Sep
15
2020
--

Data virtualization service Varada raises $12M

Varada, a Tel Aviv-based startup that focuses on making it easier for businesses to query data across services, today announced that it has raised a $12 million Series A round led by Israeli early-stage fund MizMaa Ventures, with participation by Gefen Capital.

“If you look at the storage aspect for big data, there’s always innovation, but we can put a lot of data in one place,” Varada CEO and co-founder Eran Vanounou told me. “But translating data into insight? It’s so hard. It’s costly. It’s slow. It’s complicated.”

That’s a lesson he learned during his time as CTO of LivePerson, which he described as a classic big data company. And just like at LivePerson, where the team had to reinvent the wheel to solve its data problems, again and again, every company — and not just the large enterprises — now struggles with managing their data and getting insights out of it, Vanounou argued.

varada architecture diagram

Image Credits: Varada

The rest of the founding team, David Krakov, Roman Vainbrand and Tal Ben-Moshe, already had a lot of experience in dealing with these problems, too, with Ben-Moshe having served at the chief software architect of Dell EMC’s XtremIO flash array unit, for example. They built the system for indexing big data that’s at the core of Varada’s platform (with the open-source Presto SQL query engine being one of the other cornerstones).

Image Credits: Varada

Essentially, Varada embraces the idea of data lakes and enriches that with its indexing capabilities. And those indexing capabilities is where Varada’s smarts can be found. As Vanounou explained, the company is using a machine learning system to understand when users tend to run certain workloads, and then caches the data ahead of time, making the system far faster than its competitors.

“If you think about big organizations and think about the workloads and the queries, what happens during the morning time is different from evening time. What happened yesterday is not what happened today. What happened on a rainy day is not what happened on a shiny day. […] We listen to what’s going on and we optimize. We leverage the indexing technology. We index what is needed when it is needed.”

That helps speed up queries, but it also means less data has to be replicated, which also brings down the cost. As MizMaa’s Aaron Applbaum noted, since Varada is not a SaaS solution, the buyers still get all of the discounts from their cloud providers, too.

In addition, the system can allocate resources intelligently so that different users can tap into different amounts of bandwidth. You can tell it to give customers more bandwidth than your financial analysts, for example.

“Data is growing like crazy: in volume, in scale, in complexity, in who requires it and what the business intelligence uses are, what the API uses are,” Applbaum said when I asked him why he decided to invest. “And compute is getting slightly cheaper, but not really, and storage is getting cheaper. So if you can make the trade-off to store more stuff, and access things more intelligently, more quickly, more agile — that was the basis of our thesis, as long as you can do it without compromising performance.”

Varada, with its team of experienced executives, architects and engineers, ticked a lot of the company’s boxes in this regard, but he also noted that unlike some other Israeli startups, the team understood that it had to listen to customers and understand their needs, too.

“In Israel, you have a history — and it’s become less and less the case — but historically, there’s a joke that it’s ‘ready, fire, aim.’ You build a technology, you’ve got this beautiful thing and you’re like, ‘alright, we did it,’ but without listening to the needs of the customer,” he explained.

The Varada team is not afraid to compare itself to Snowflake, which at least at first glance seems to make similar promises. Vananou praised the company for opening up the data warehousing market and proving that people are willing to pay for good analytics. But he argues that Varada’s approach is fundamentally different.

“We embrace the data lake. So if you are Mr. Customer, your data is your data. We’re not going to take it, move it, copy it. This is your single source of truth,” he said. And in addition, the data can stay in the company’s virtual private cloud. He also argues that Varada isn’t so much focused on the business users but the technologists inside a company.

 

Feb
24
2020
--

Databricks makes bringing data into its ‘lakehouse’ easier

Databricks today announced the launch of its new Data Ingestion Network of partners and the launch of its Databricks Ingest service. The idea here is to make it easier for businesses to combine the best of data warehouses and data lakes into a single platform — a concept Databricks likes to call “lakehouse.”

At the core of the company’s lakehouse is Delta Lake, Databricks’ Linux Foundation-managed open-source project that brings a new storage layer to data lakes that helps users manage the lifecycle of their data and ensures data quality through schema enforcement, log records and more. Databricks users can now work with the first five partners in the Ingestion Network — Fivetran, Qlik, Infoworks, StreamSets, Syncsort — to automatically load their data into Delta Lake. To ingest data from these partners, Databricks customers don’t have to set up any triggers or schedules — instead, data automatically flows into Delta Lake.

“Until now, companies have been forced to split up their data into traditional structured data and big data, and use them separately for BI and ML use cases. This results in siloed data in data lakes and data warehouses, slow processing and partial results that are too delayed or too incomplete to be effectively utilized,” says Ali Ghodsi, co-founder and CEO of Databricks. “This is one of the many drivers behind the shift to a Lakehouse paradigm, which aspires to combine the reliability of data warehouses with the scale of data lakes to support every kind of use case. In order for this architecture to work well, it needs to be easy for every type of data to be pulled in. Databricks Ingest is an important step in making that possible.”

Databricks VP of Product Marketing Bharath Gowda also tells me that this will make it easier for businesses to perform analytics on their most recent data and hence be more responsive when new information comes in. He also noted that users will be able to better leverage their structured and unstructured data for building better machine learning models, as well as to perform more traditional analytics on all of their data instead of just a small slice that’s available in their data warehouse.

Dec
17
2019
--

Satori Cyber raises $5.25M to help businesses protect their data flows

The amount of data that most companies now store — and the places they store it — continues to increase rapidly. With that, the risk of the wrong people managing to get access to this data also increases, so it’s no surprise that we’re now seeing a number of startups that focus on protecting this data and how it flows between clouds and on-premises servers. Satori Cyber, which focuses on data protecting and governance, today announced that it has raised a $5.25 million seed round led by YL Ventures.

“We believe in the transformative power of data to drive innovation and competitive advantage for businesses,” the company says. “We are also aware of the security, privacy and operational challenges data-driven organizations face in their journey to enable broad and optimized data access for their teams, partners and customers. This is especially true for companies leveraging cloud data technologies.”

Satori is officially coming out of stealth mode today and launching its first product, the Satori Cyber Secure Data Access Cloud. This service provides enterprises with the tools to provide access controls for their data, but maybe just as importantly, it also offers these companies and their security teams visibility into their data flows across cloud and hybrid environments. The company argues that data is “a moving target” because it’s often hard to know how exactly it moves between services and who actually has access to it. With most companies now splitting their data between lots of different data stores, that problem only becomes more prevalent over time and continuous visibility becomes harder to come by.

“Until now, security teams have relied on a combination of highly segregated and restrictive data access and one-off technology-specific access controls within each data store, which has only slowed enterprises down,” said Satori Cyber CEO and co-founder Eldad Chai. “The Satori Cyber platform streamlines this process, accelerates data access and provides a holistic view across all organizational data flows, data stores and access, as well as granular access controls, to accelerate an organization’s data strategy without those constraints.”

Both co-founders (Chai and CTO Yoav Cohen) previously spent nine years building security solutions at Imperva and Incapsula (which acquired Imperva in 2014). Based on this experience, they understood that onboarding had to be as easy as possible and that operations would have to be transparent to the users. “We built Satori’s Secure Data Access Cloud with that in mind, and have designed the onboarding process to be just as quick, easy and painless. On-boarding Satori involves a simple host name change and does not require any changes in how your organizational data is accessed or used,” they explain.

Apr
02
2019
--

How to handle dark data compliance risk at your company

Slack and other consumer-grade productivity tools have been taking off in workplaces large and small — and data governance hasn’t caught up.

Whether it’s litigation, compliance with regulations like GDPR or concerns about data breaches, legal teams need to account for new types of employee communication. And that’s hard when work is happening across the latest messaging apps and SaaS products, which make data searchability and accessibility more complex.

Here’s a quick look at the problem, followed by our suggestions for best practices at your company.

Problems

The increasing frequency of reported data breaches and expanding jurisdiction of new privacy laws are prompting conversations about dark data and risks at companies of all sizes, even small startups. Data risk discussions necessarily include the risk of a data breach, as well as preservation of data. Just two weeks ago it was reported that Jared Kushner used WhatsApp for official communications and screenshots of those messages for preservation, which commentators say complies with record keeping laws but raises questions about potential admissibility as evidence.

Aug
29
2018
--

Storage provider Cloudian raises $94M

Cloudian, a company that specializes in helping businesses store petabytes of data, today announced that it has raised a $94 million Series E funding round. Investors in this round, which is one of the largest we have seen for a storage vendor, include Digital Alpha, Fidelity Eight Roads, Goldman Sachs, INCJ, JPIC (Japan Post Investment Corporation), NTT DOCOMO Ventures and WS Investments. This round includes a $25 million investment from Digital Alpha, which was first announced earlier this year.

With this, the seven-year-old company has now raised a total of $174 million.

As the company told me, it now has about 160 employees and 240 enterprise customers. Cloudian has found its sweet spot in managing the large video archives of entertainment companies, but its customers also include healthcare companies, automobile manufacturers and Formula One teams.

What’s important to stress here is that Cloudian’s focus is on on-premise storage, not cloud storage, though it does offer support for multi-cloud data management, as well. “Data tends to be most effectively used close to where it is created and close to where it’s being used,” Cloudian VP of worldwide sales Jon Ash told me. “That’s because of latency, because of network traffic. You can almost always get better performance, better control over your data if it is being stored close to where it’s being used.” He also noted that it’s often costly and complex to move that data elsewhere, especially when you’re talking about the large amounts of information that Cloudian’s customers need to manage.

Unsurprisingly, companies that have this much data now want to use it for machine learning, too, so Cloudian is starting to get into this space, as well. As Cloudian CEO and co-founder Michael Tso also told me, companies are now aware that the data they pull in, whether from IoT sensors, cameras or medical imaging devices, will only become more valuable over time as they try to train their models. If they decide to throw the data away, they run the risk of having nothing with which to train their models.

Cloudian plans to use the new funding to expand its global sales and marketing efforts and increase its engineering team. “We have to invest in engineering and our core technology, as well,” Tso noted. “We have to innovate in new areas like AI.”

As Ash also stressed, Cloudian’s business is really data management — not just storage. “Data is coming from everywhere and it’s going everywhere,” he said. “The old-school storage platforms that were siloed just don’t work anywhere.”

Feb
28
2017
--

Reflect drops public beta to power developer-first data visualization

Abstract pattern of yellow pie charts on multiColored background of geometric shapes Data visualization has been done — we have publicly traded, interactive, real-time and heck even artificially intelligent companies promising data visualization. But despite all the noise, Portland-based Reflect is making a go of it in the space, opening up its public beta today. By putting developers first and letting them integrate and customize visualizations in their own… Read More

Nov
30
2016
--

Amazon will truck your massive piles of data to the cloud with an 18-wheeler

img_20161130_103941 Meet AWS Snowmobile, a tractor-trailer for when your big data is just too damn big. The truck houses a container that can store up to 100 petabytes of data. Real-life data hoarders can contract Amazon to move exabytes of data to the cloud using the new tricked-out trucks. Snowmobile attaches directly to your data center with power and network fibre to move critical information to AWS,… Read More

Powered by WordPress | Theme: Aeros 2.0 by TheBuckmaker.com