Sep
16
2021
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The Org nabs $20M led by Tiger Global to expand its platform based on public organizational charts

LinkedIn normalized the idea of making people’s resume’s visible to anyone who wanted to look at them, and today a startup that’s hoping to do the same for companies and how they are organized and run is announcing some funding. The Org, which wants to build a global, publicly viewable database of company organizational charts — and then utilize that database as a platform to power a host of other services — has raised $20 million, money that it will be using to hire more people, add on more org charts and launch new features, with a recruitment toolkit being first on the list.

The Series B is led by Tiger Global, with previous backers Sequoia, Founders Fund and Balderton Capital also participating alongside new investors Thursday Ventures, Lars Fjeldsoe-Nielsen (a former Balderton partner), Neeraj Arora (formative early WhatsApp exec), investor Gavin Baker, and more. From what we understand, the investment values The Org at $100 million.

Founders Fund led the company’s last round, a Series A in February 2020, and the whole world of work has really changed a lot in the interim because of COVID-19: companies have become more distributed (a result of offices shutting down); the make-up of businesses has changed because of new demands; and many of us have had our sense of connection to our jobs tested in ways that we never thought it would.

All of that has had a massive impact on The Org, and has played into its theory of why org charts are useful, and most useful as a tool for transparency.

“In many ways the pandemic has forced us to reevaluate the norms of how work happens. One of the misconceptions was the idea that you are only working when you are at the office, 9-5. But the future of work is a hybrid set up but you get a lot of issues that arise out of that, communication being one of them. Now it’s much more important to create alignment, a sense of connection, and really feeling a sense of belonging in your company,” Christian Wylonis, the CEO who co-founded the company with Andreas Jarbøl, said in an interview (the two are pictured below). “We think that a lot of these issues are rooted around transparency and that is what The Org is about. Who is doing what, and why?”

Image Credits: The Org

He said that when the coronavirus suddenly ramped up into a global issue — and it really was sudden; our conversation in February 2020 had nothing whatsoever to do with it, yet it was only weeks later that everything shut down — it wasn’t obvious that The Org would have a place in the so-called “new normal.”

“We were as nervous as anyone else, but the idea of what work would look like and how we enable people around that has gotten a lot higher on the agenda,” he said. “The appetite for new tools has improved dramatically, and we can see that in our traffic.”

The Org has indeed seen some very impressive growth. The company now hosts some 130,000 public org charts, sees 30,000 daily visitors and has more than 120,000 registered users. And more casual usage has boomed, too. Wylonis notes that The Org now has close to 1 million visitors each month versus just 100,000 in February 2020, when it only had 16,000 org charts on its platform.

Monetization is coming slowly for the startup. Building, editing and officially “claiming” a profile on the platform are all still free, but in the meantime The Org is working on its platform play and using the database that it is building to power other services. Job hunting is the first area that it will tackle.

Posting jobs will be free, and it’s integrating with Greenhouse to feed information into its system, but recruiters and HR pros are given an option to manage the sourcing and screening process through The Org, a kind of executive recruitment tool, which will come at a charge. Down the line there are plans for more communications and HR tools, Wylonis said. Some of this will be built by way of integrations and APIs with other services, and some tools — such as communications features — will be built in-house, from the ground up.

When I covered the company’s last round, I’d noted that there were some obvious hurdles for The Org, as well as potentially others like Charthop or Visier building business models on providing more transparency and information around hiring and how companies are run.

Sometimes the companies in question don’t actually want to have more transparency. And any database that is based around self-reporting runs the risk of being only as good as the data that is put into it — meaning it may be incomplete, or simply wrong, or just presented to the contributors’ best advantage, not that of the company itself. (This is one of the issues with LinkedIn, too: Even with people’s resumes being public, it’s still very easy to lie about what you actually do, or have done.)

So far, the theory is that some of this will be resolved by way of who The Org is targeting and how it is growing. Today the company’s “sweet spot” is early-stage startups with about 50-200 employees, and generally org charts are created for these businesses in part by The Org itself, and then largely by way of wiki-style user-edited content (anyone with a company email can get involved).

The plan is both to continue working with those smaller startups as they scale up, but also target bigger and bigger businesses. These, however, can be trickier to snag — not least because they will stretch into the realm of public companies, but also because their charts will be more complicated to map and manage consistently. For that reason, The Org is also adding in more features around how companies can “claim” their profiles, including managing permissions for who can edit profiles.

This might mean more managed public profiles, but the idea is that it will be a start, and once more companies post more information, we will see more transparency overall, not unlike how LinkedIn evolved, Wylonis said.

The LinkedIn analogy is interesting for another reason. It seems a no-brainer that LinkedIn, which is at its heart a massive database of information about the world of professional work, and the people and companies involved in it, would have wanted to build its own version of org charts at some point. And yet it hasn’t.

Some of this might be down to how LinkedIn has fundamentally built and organised its own database and knowledge graph, but Wylonis believes it might also be a conceptual difference.

“We think that this might be the fundamental difference between us and them,” Wylonis said of LinkedIn. “They are a database of resumes. ‘I can say whatever I want.’ But for us, the atomic unit is the organization itself. That is an important distinction because it’s a one to many relationship. It can’t be only me editing my profile. And allows us to build structures.”

He added that this was one of the reasons that Keith Rabois — who was an early exec at LinkedIn — became an early investor in The Org: “LinkedIn has been looking at this forever, but they haven’t been able to build it, and so that is how we caught his attention.”

Sep
08
2021
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Real-time database platform SingleStore raises $80M more, now at a $940M valuation

Organizations are swimming in data these days, and so solutions to help manage and use that data in more efficient ways will continue to see a lot of attention and business. In the latest development, SingleStore — which provides a platform to enterprises to help them integrate, monitor and query their data as a single entity, regardless of whether that data is stored in multiple repositories — is announcing another $80 million in funding, money that it will be using to continue investing in its platform, hiring more talent and overall business expansion. Sources close to the company tell us that the company’s valuation has grown to $940 million.

The round, a Series F, is being led by Insight Partners, with new investor Hewlett Packard Enterprise, and previous backers Khosla Ventures, Dell Technologies Capital, Rev IV, Glynn Capital and GV (formerly Google Ventures) also participating. The startup has to date raised $264 million, including most recently an $80 million Series E last December, just on the heels of rebranding from MemSQL.

The fact that there are three major strategic investors in this Series F — HPE, Dell and Google — may say something about the traction that SingleStore is seeing, but so too do its numbers: 300%+ increase in new customer acquisition for its cloud service and 150%+ year-over-year growth in cloud.

Raj Verma, SingleStore’s CEO, said in an interview that its cloud revenues have grown by 150% year over year and now account for some 40% of all revenues (up from 10% a year ago). New customer numbers, meanwhile, have grown by over 300%.

“The flywheel is now turning around,” Verma said. “We didn’t need this money. We’ve barely touched our Series E. But I think there has been a general sentiment among our board and management that we are now ready for the prime time. We think SingleStore is one of the best-kept secrets in the database market. Now we want to aggressively be an option for people looking for a platform for intensive data applications or if they want to consolidate databases to one from three, five or seven repositories. We are where the world is going: real-time insights.”

With database management and the need for more efficient and cost-effective tools to manage that becoming an ever-growing priority — one that definitely got a fillip in the last 18 months with COVID-19 pushing people into more remote working environments. That means SingleStore is not without competitors, with others in the same space, including Amazon, Microsoft, Snowflake, PostgreSQL, MySQL, Redis and more. Others like Firebolt are tackling the challenges of handing large, disparate data repositories from another angle. (Some of these, I should point out, are also partners: SingleStore works with data stored on AWS, Microsoft Azure, Google Cloud Platform and Red Hat, and Verma describes those who do compute work as “not database companies; they are using their database capabilities for consumption for cloud compute.”)

But the company has carved a place for itself with enterprises and has thousands now on its books, including GE, IEX Cloud, Go Guardian, Palo Alto Networks, EOG Resources and SiriusXM + Pandora.

“SingleStore’s first-of-a-kind cloud database is unmatched in speed, scale, and simplicity by anything in the market,” said Lonne Jaffe, managing director at Insight Partners, in a statement. “SingleStore’s differentiated technology allows customers to unify real-time transactions and analytics in a single database.” Vinod Khosla from Khosla Ventures added that “SingleStore is able to reduce data sprawl, run anywhere, and run faster with a single database, replacing legacy databases with the modern cloud.”

Aug
31
2021
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Databricks raises $1.6B at $38B valuation as it blasts past $600M ARR

Databricks this morning confirmed earlier reports that it was raising new capital at a higher valuation. The data- and AI-focused company has secured a $1.6 billion round at a $38 billion valuation, it said. Bloomberg first reported last week that Databricks was pursuing new capital at that price.

The Series H was led by Counterpoint Global, a Morgan Stanley fund. Other new investors included Baillie Gifford, UC Investments and ClearBridge. A grip of prior investors also kicked in cash to the round.

The new funding brings Databricks’ total private funding raised to $3.5 billion. Notably, its latest raise comes just seven months after the late-stage startup raised $1 billion on a $28 billion valuation. Its new valuation represents paper value creation in excess of $1 billion per month.

The company, which makes open source and commercial products for processing structured and unstructured data in one location, views its market as a new technology category. Databricks calls the technology a data “lakehouse,” a mashup of data lake and data warehouse.

Databricks CEO and co-founder Ali Ghodsi believes that its new capital will help his company secure market leadership.

For context, since the 1980s, large companies have stored massive amounts of structured data in data warehouses. More recently, companies like Snowflake and Databricks have provided a similar solution for unstructured data called a data lake.

In Ghodsi’s view, combining structured and unstructured data in a single place with the ability for customers to execute data science and business-intelligence work without moving the underlying data is a critical change in the larger data market.

“[Data lakehouses are] a new category, and we think there’s going to be lots of vendors in this data category. So it’s a land grab. We want to quickly race to build it and complete the picture,” he said in an interview with TechCrunch.

Ghodsi also pointed out that he is going up against well-capitalized competitors and that he wants the funds to compete hard with them.

“And you know, it’s not like we’re up against some tiny startups that are getting seed funding to build this. It’s all kinds of [large, established] vendors,” he said. That includes Snowflake, Amazon, Google and others who want to secure a piece of the new market category that Databricks sees emerging.

The company’s performance indicates that it’s onto something.

Growth

Databricks has reached the $600 million annual recurring revenue (ARR) milestone, it disclosed as part of its funding announcement. It closed 2020 at $425 million ARR, to better illustrate how quickly it is growing at scale.

Per the company, its new ARR figure represents 75% growth, measured on a year-over-year basis.

That’s quick for a company of its size; per the Bessemer Cloud Index, top-quartile public software companies are growing at around 44% year over year. Those companies are worth around 22x their forward revenues.

At its new valuation, Databricks is worth 63x its current ARR. So Databricks isn’t cheap, but at its current pace should be able to grow to a size that makes its most recent private valuation easily tenable when it does go public, provided that it doesn’t set a new, higher bar for its future performance by raising again before going public.

Ghodsi declined to share timing around a possible IPO, and it isn’t clear whether the company will pursue a traditional IPO or if it will continue to raise private funds so that it can direct list when it chooses to float. Regardless, Databricks is now sufficiently valuable that it can only exit to one of a handful of mega-cap technology giants or go public.

Why hasn’t the company gone public? Ghodsi is enjoying a rare position in the startup market: He has access to unlimited capital. Databricks had to open another $100 million in its latest round, which was originally set to close at just $1.5 billion. It doesn’t lack for investor interest, allowing its CEO to bring aboard the sort of shareholder he wants for his company’s post-IPO life — while enjoying limited dilution.

This also enables him to hire aggressively, possibly buy some smaller companies to fill in holes in Databricks’ product roadmap, and grow outside of the glare of Wall Street expectations from a position of capital advantage. It’s the startup equivalent of having one’s cake and eating it too.

But staying private longer isn’t without risks. If the larger market for software companies was rapidly devalued, Databricks could find itself too expensive to go public at its final private valuation. However, given the long bull market that we’ve seen in recent years for software shares, and the confidence Ghodsi has in his potential market, that doesn’t seem likely.

There’s still much about Databricks’ financial position that we don’t yet know — its gross margin profile, for example. TechCrunch is also incredibly curious what all its fundraising and ensuing spending have done to near-term Databricks operating cash flow results, as well as how long its gross-margin adjusted CAC payback has evolved since the onset of COVID-19. If we ever get an S-1, we might find out.

For now, winsome private markets are giving Ghodsi and crew space to operate an effectively public company without the annoyances that come with actually being public. Want the same thing for your company? Easy: Just reach $600 million ARR while growing 75% year over year.

Jul
15
2021
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The CockroachDB EC-1

Every application is a palimpsest of technologies, each layer forming a base that enables the next layer to function. Web front ends rely on JavaScript and browser DOM, which rely on back-end APIs, which themselves rely on databases.

As one goes deeper down the stack, engineering decisions become ever more conservative — changing the location of a button in a web app is an inconvenience; changing a database engine can radically upend an entire project.

It’s little surprise then that database technologies are among the longest-lasting engineering projects in the modern software developer toolkit. MySQL, which remains one of the most popular database engines in the world, was first released in the mid-1990s, and Oracle Database, launched more than four decades ago, is still widely used in high-performance corporate environments.

Database technology can change the world, but the world in these parts changes very, very slowly. That’s made building a startup in the sector a tough equation: Sales cycles can be painfully slow, even when new features can dramatically expand a developer’s capabilities. Competition is stiff and comes from some of the largest and most entrenched tech companies in the world. Exits have also been few and far between.

That challenge — and opportunity — is what makes studying Cockroach Labs so interesting. The company behind CockroachDB attempts to solve a long-standing problem in large-scale, distributed database architecture: How to make it so that data created in one place on the planet is always available for consumption by applications that are thousands of miles away, immediately and accurately. Making global data always available immediately and accurately might sound like a simple use case, but in reality it’s quite the herculean task. Cockroach Labs’ story is one of an uphill struggle, but one that saw it turn into a next-generation, $2-billion-valued database contender.

The lead writer of this EC-1 is Bob Reselman. Reselman has been writing about the enterprise software market for more than two decades, with a particular emphasis on teaching and educating engineers on technology. The lead editor for this package was Danny Crichton, the assistant editor was Ram Iyer, the copy editor was Richard Dal Porto, figures were designed by Bob Reselman and stylized by Bryce Durbin, and illustrations were drawn by Nigel Sussman.

CockroachDB had no say in the content of this analysis and did not get advance access to it. Reselman has no financial ties to CockroachDB or other conflicts of interest to disclose.

The CockroachDB EC-1 comprises four main articles numbering 9,100 words and a reading time of 37 minutes. Here’s what we’ll be crawling over:

We’re always iterating on the EC-1 format. If you have questions, comments or ideas, please send an email to TechCrunch Managing Editor Danny Crichton at danny@techcrunch.com.

Jul
15
2021
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How engineers fought the CAP theorem in the global war on latency

CockroachDB was intended to be a global database from the beginning. The founders of Cockroach Labs wanted to ensure that data written in one location would be viewable immediately in another location 10,000 miles away. The use case was simple, but the work needed to make it happen was herculean.

The company is betting the farm that it can solve one of the largest challenges for web-scale applications. The approach it’s taking is clever, but it’s a bit complicated, particularly for the non-technical reader. Given its history and engineering talent, the company is in the process of pulling it off and making a big impact on the database market, making it a technology well worth understanding. In short, there’s value in digging into the details.

Using CockroachDB’s multiregion feature to segment data according to geographic proximity fulfills Cockroach Labs’ primary directive: To get data as close to the user as possible.

In part 1 of this EC-1, I provided a general overview and a look at the origins of Cockroach Labs. In this installment, I’m going to cover the technical details of the technology with an eye to the non-technical reader. I’m going to describe the CockroachDB technology through three questions:

  1. What makes reading and writing data over a global geography so hard?
  2. How does CockroachDB address the problem?
  3. What does it all mean for those using CockroachDB?

What makes reading and writing data over a global geography so hard?

Spencer Kimball, CEO and co-founder of Cockroach Labs, describes the situation this way:

There’s lots of other stuff you need to consider when building global applications, particularly around data management. Take, for example, the question and answer website Quora. Let’s say you live in Australia. You have an account and you store the particulars of your Quora user identity on a database partition in Australia.

But when you post a question, you actually don’t want that data to just be posted in Australia. You want that data to be posted everywhere so that all the answers to all the questions are the same for everybody, anywhere. You don’t want to have a situation where you answer a question in Sydney and then you can see it in Hong Kong, but you can’t see it in the EU. When that’s the case, you end up getting different answers depending where you are. That’s a huge problem.

Reading and writing data over a global geography is challenging for pretty much the same reason that it’s faster to get a pizza delivered from across the street than from across the city. The essential constraints of time and space apply. Whether it’s digital data or a pepperoni pizza, the further away you are from the source, the longer stuff takes to get to you.

Jul
15
2021
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Scaling CockroachDB in the red ocean of relational databases

Most database startups avoid building relational databases, since that market is dominated by a few goliaths. Oracle, MySQL and Microsoft SQL Server have embedded themselves into the technical fabric of large- and medium-size companies going back decades. These established companies have a lot of market share and a lot of money to quash the competition.

So rather than trying to compete in the relational database market, over the past decade, many database startups focused on alternative architectures such as document-centric databases (like MongoDB), key-value stores (like Redis) and graph databases (like Neo4J). But Cockroach Labs went against conventional wisdom with CockroachDB: It intentionally competed in the relational database market with its relational database product.

While it did face an uphill battle to penetrate the market, Cockroach Labs saw a surprising benefit: It didn’t have to invent a market. All it needed to do was grab a share of a market that also happened to be growing rapidly.

Cockroach Labs has a bright future, compelling technology, a lot of money in the bank and has an experienced, technically astute executive team.

In previous parts of this EC-1, I looked at the origins of CockroachDB, presented an in-depth technical description of its product as well as an analysis of the company’s developer relations and cloud service, CockroachCloud. In this final installment, we’ll look at the future of the company, the competitive landscape within the relational database market, its ability to retain talent as it looks toward a potential IPO or acquisition, and the risks it faces.

CockroachDB’s success is not guaranteed. It has to overcome significant hurdles to secure a profitable place for itself among a set of well-established database technologies that are owned by companies with very deep pockets.

It’s not impossible, though. We’ll first look at MongoDB as an example of how a company can break through the barriers for database startups competing with incumbents.

When life gives you Mongos, make MongoDB

Dev Ittycheria, MongoDB CEO, rings the Nasdaq Stock Market Opening Bell. Image Credits: Nasdaq, Inc

MongoDB is a good example of the risks that come with trying to invent a new database market. The company started out as a purely document-centric database at a time when that approach was the exception rather than the rule.

Web developers like document-centric databases because they address a number of common use cases in their work. For example, a document-centric database works well for storing comments to a blog post or a customer’s entire order history and profile.

Apr
13
2021
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Meroxa raises $15M Series A for its real-time data platform

Meroxa, a startup that makes it easier for businesses to build the data pipelines to power both their analytics and operational workflows, today announced that it has raised a $15 million Series A funding round led by Drive Capital. Existing investors Root, Amplify and Hustle Fund also participated in this round, which together with the company’s previously undisclosed $4.2 million seed round now brings total funding in the company to $19.2 million.

The promise of Meroxa is that businesses can use a single platform for their various data needs and won’t need a team of experts to build their infrastructure and then manage it. At its core, Meroxa provides a single software-as-a-service solution that connects relational databases to data warehouses and then helps businesses operationalize that data.

Image Credits: Meroxa

“The interesting thing is that we are focusing squarely on relational and NoSQL databases into data warehouse,” Meroxa co-founder and CEO DeVaris Brown told me. “Honestly, people come to us as a real-time FiveTran or real-time data warehouse sink. Because, you know, the industry has moved to this [extract, load, transform] format. But the beautiful part about us is, because we do change data capture, we get that granular data as it happens.” And businesses want this very granular data to be reflected inside of their data warehouses, Brown noted, but he also stressed that Meroxa can expose this stream of data as an API endpoint or point it to a Webhook.

The company is able to do this because its core architecture is somewhat different from other data pipeline and integration services that, at first glance, seem to offer a similar solution. Because of this, users can use the service to connect different tools to their data warehouse but also build real-time tools on top of these data streams.

Image Credits: Meroxa

“We aren’t a point-to-point solution,” Meroxa co-founder and CTO Ali Hamidi explained. “When you set up the connection, you aren’t taking data from Postgres and only putting it into Snowflake. What’s really happening is that it’s going into our intermediate stream. Once it’s in that stream, you can then start hanging off connectors and say, ‘Okay, well, I also want to peek into the stream, I want to transfer my data, I want to filter out some things, I want to put it into S3.’ ”

Because of this, users can use the service to connect different tools to their data warehouse but also build real-time tools to utilize the real-time data stream. With this flexibility, Hamidi noted, a lot of the company’s customers start with a pretty standard use case and then quickly expand into other areas as well.

Brown and Hamidi met during their time at Heroku, where Brown was a director of product management and Hamidi a lead software engineer. But while Heroku made it very easy for developers to publish their web apps, there wasn’t anything comparable in the highly fragmented database space. The team acknowledges that there are a lot of tools that aim to solve these data problems, but few of them focus on the user experience.

Image Credits: Meroxa

“When we talk to customers now, it’s still very much an unsolved problem,” Hamidi said. “It seems kind of insane to me that this is such a common thing and there is no ‘oh, of course you use this tool because it addresses all my problems.’ And so the angle that we’re taking is that we see user experience not as a nice-to-have, it’s really an enabler, it is something that enables a software engineer or someone who isn’t a data engineer with 10 years of experience in wrangling Kafka and Postgres and all these things. […] That’s a transformative kind of change.”

It’s worth noting that Meroxa uses a lot of open-source tools but the company has also committed to open-sourcing everything in its data plane as well. “This has multiple wins for us, but one of the biggest incentives is in terms of the customer, we’re really committed to having our agenda aligned. Because if we don’t do well, we don’t serve the customer. If we do a crappy job, they can just keep all of those components and run it themselves,” Hamidi explained.

Today, Meroxa, which the team founded in early 2020, has more than 24 employees (and is 100% remote). “I really think we’re building one of the most talented and most inclusive teams possible,” Brown told me. “Inclusion and diversity are very, very high on our radar. Our team is 50% black and brown. Over 40% are women. Our management team is 90% underrepresented. So not only are we building a great product, we’re building a great company, we’re building a great business.”  

Feb
17
2021
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TigerGraph raises $105M Series C for its enterprise graph database

TigerGraph, a well-funded enterprise startup that provides a graph database and analytics platform, today announced that it has raised a $105 million Series C funding round. The round was led by Tiger Global and brings the company’s total funding to over $170 million.

“TigerGraph is leading the paradigm shift in connecting and analyzing data via scalable and native graph technology with pre-connected entities versus the traditional way of joining large tables with rows and columns,” said TigerGraph founder and CEO, Yu Xu. “This funding will allow us to expand our offering and bring it to many more markets, enabling more customers to realize the benefits of graph analytics and AI.”

Current TigerGraph customers include the likes of Amgen, Citrix, Intuit, Jaguar Land Rover and UnitedHealth Group. Using a SQL-like query language (GSQL), these customers can use the company’s services to store and quickly query their graph databases. At the core of its offerings is the TigerGraphDB database and analytics platform, but the company also offers a hosted service, TigerGraph Cloud, with pay-as-you-go pricing, hosted either on AWS or Azure. With GraphStudio, the company also offers a graphical UI for creating data models and visually analyzing them.

The promise for the company’s database services is that they can scale to tens of terabytes of data with billions of edges. Its customers use the technology for a wide variety of use cases, including fraud detection, customer 360, IoT, AI and machine learning.

Like so many other companies in this space, TigerGraph is facing some tailwind thanks to the fact that many enterprises have accelerated their digital transformation projects during the pandemic.

“Over the last 12 months with the COVID-19 pandemic, companies have embraced digital transformation at a faster pace driving an urgent need to find new insights about their customers, products, services, and suppliers,” the company explains in today’s announcement. “Graph technology connects these domains from the relational databases, offering the opportunity to shrink development cycles for data preparation, improve data quality, identify new insights such as similarity patterns to deliver the next best action recommendation.”

Sep
22
2020
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Microsoft brings data services to its Arc multi-cloud management service

Microsoft today launched a major update to its Arc multi-cloud service that allows Azure customers to run and manage workloads across clouds — including those of Microsoft’s competitors — and their on-premises data centers. First announced at Microsoft Ignite in 2019, Arc was always meant to not just help users manage their servers but also allow them to run data services like Azure SQL and Azure Database for PostgreSQL, close to where their data sits.

Today, the company is making good on this promise with the preview launch of Azure Arc-enabled data services with support for, as expected, Azure SQL and Azure Database for PostgreSQL.

In addition, Microsoft is making the core feature of Arc, Arc-enabled servers, generally available. These are the tools at the core of the service that allow enterprises that use the standard Azure Portal to manage and monitor their Windows and Linux servers across their multi-cloud and edge environments.

Image Credits: Microsoft

“We’ve always known that enterprises are looking to unlock the agility of the cloud — they love the app model, they love the business model — while balancing a need to maintain certain applications and workloads on premises,” Rohan Kumar, Microsoft’s corporate VP for Azure Data said. “A lot of customers actually have a multi-cloud strategy. In some cases, they need to keep the data specifically for regulatory compliance. And in many cases, they want to maximize their existing investments. They’ve spent a lot of CapEx.”

As Kumar stressed, Microsoft wants to meet customers where they are, without forcing them to adopt a container architecture, for example, or replace their specialized engineered appliances to use Arc.

“Hybrid is really [about] providing that flexible choice to our customers, meeting them where they are, and not prescribing a solution,” he said.

He admitted that this approach makes engineering the solution more difficult, but the team decided the baseline should be a container endpoint and nothing more. And for the most part, Microsoft packaged up the tools its own engineers were already using to run Azure services on the company’s own infrastructure to manage these services in a multi-cloud environment.

“In hindsight, it was a little challenging at the beginning, because, you can imagine, when we initially built them, we didn’t imagine that we’ll be packaging them like this. But it’s a very modern design point,” Kumar said. But the result is that supporting customers is now relatively easy because it’s so similar to what the team does in Azure, too.

Kumar noted that one of the selling points for the Azure Data Services is also that the version of Azure SQL is essentially evergreen, allowing them to stop worrying about SQL Server licensing and end-of-life support questions.

Jun
15
2020
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VESoft raises $8M to meet China’s growing need for graph databases

Sherman Ye founded VESoft in 2018 when he saw a growing demand for graph databases in China. Its predecessors, like Neo4j and TigerGraph, had already been growing aggressively in the West for a few years, while China was just getting to know the technology that leverages graph structures to store data sets and depict their relationships, such as those used for social media analysis, e-commerce recommendations and financial risk management.

VESoft is ready for further growth after closing an $8 million funding round led by Redpoint China Ventures, an investment firm launched by Silicon Valley-based Redpoint Ventures in 2005. Existing investor Matrix Partners China also participated in the Series pre-A round. The new capital will allow the startup to develop products and expand to markets in North America, Europe and other parts of Asia.

The 30-people team is comprised of former employees from Alibaba, Facebook, Huawei and IBM. It’s based in Hangzhou, a scenic city known for its rich history and housing Alibaba and its financial affiliate Ant Financial, where Ye previously worked as a senior engineer after his four-year stint with Facebook in California. From 2017 to 2018, the entrepreneur noticed that Ant Financial’s customers were increasingly interested in adopting graph databases as an alternative to relational databases, a model that had been popular since the 80s and normally organizes data into tables.

“While relational databases are capable of achieving many functions carried out by graph databases… they deteriorate in performance as the quantity of data grows,” Ye told TechCrunch during an interview. “We didn’t use to have so much data.”

Information explosion is one reason why Chinese companies are turning to graph databases, which can handle millions of transactions to discover patterns within scattered data. The technology’s rise is also a response to new forms of online businesses that depend more on relationships.

“Take recommendations for example. The old model recommends content based purely on user profiles, but the problem of relying on personal browsing history is it fails to recommend new things. That was fine for a long time as the Chinese [internet] market was big enough to accommodate many players. But as the industry becomes saturated and crowded… companies need to ponder how to retain existing users, lengthen their time spent, and win users from rivals.”

The key lies in serving people content and products they find appealing. Graph databases come in handy, suggested Ye, when services try to predict users’ interest or behavior as the model uncovers what their friends or people within their social circles like. “That’s a lot more effective than feeding them what’s trending.”

Neo4j compares relational and graph databases (Link)

The company has made its software open source, which the founder believed can help cultivate a community of graph database users and educate the market in China. It will also allow VESoft to reach more engineers in the English-speaking world who are well-acquainted with the open-source culture.

“There is no such thing as being ‘international’ or ‘domestic’ for a technology-driven company. There are no boundaries between countries in the open-source world,” reckoned Ye.

When it comes to generating income, the startup plans to launch a paid version for enterprises, which will come with customized plug-ins and host services.

The Nebula Graph, the brand of VESoft’s database product, is now serving 20 enterprise clients from areas across social media, e-commerce and finance, including big names like food delivery giant Meituan, popular social commerce app Xiaohongshu and e-commerce leader JD.com. A number of overseas companies are also trialing Nebula.

The time is ripe for enterprise-facing startups with a technological moat in China as the market for consumers has been divided by incumbents like Tencent and Alibaba. This makes fundraising relatively easy for VESoft. The founder is confident that Chinese companies are rapidly catching up with their Western counterparts in the space, for the gargantuan amount of data and the myriad of ways data is used in the country “will propel the technology forward.”

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