Enterprise SaaS revenue hits $100B run rate, led by Microsoft and Salesforce

In its most recent report, Synergy Research, a company that monitors cloud marketshare, found that enterprise SaaS revenue passed the $100 billion run rate this quarter. The market was led by Microsoft and Salesforce.

It shouldn’t be a surprise at this point that these two enterprise powerhouses come in at the top. Microsoft reported $10.1 billion in Productivity and Business Processes revenue, which includes Office 365, the Dynamics line and LinkedIn, the company it bought in 2016 for $26.2 billion. That $10.1 billion accounted for the top spot with 17 percent

Salesforce was next with around 12%. It announced $3.74 billion in revenue in its most recent earnings statement with Service Cloud alone accounting for $1.02 billion in revenue, crossing that billion-dollar mark for the first time.

Adobe came in third, good for around 10% market share, with $2.74 billion in revenue for its most recent report. Digital Media, which includes Creative Cloud and Document Cloud, accounted for the vast majority of the revenue with $1.8 billion. SAP and Oracle complete the top companies

SaaS Q119

A growing market

While that number may seem low, given we are 20 years into the development of the SaaS market, it is still a significant milestone, not to be dismissed lightly. As Synergy pointed out, while the market feels mature, if finds that SaaS revenue still accounts for just 20 percent of the overall enterprise software market. There’s still a long way to go, showing as with the infrastructure side of the market, things change much more slowly than we imagine, and the market is growing rapidly, as the impressive growth rates show.

“While SaaS growth rate isn’t as high as IaaS (Infrastructure as a Service) and PaaS (Platform as a Service), the SaaS market is substantially bigger and it will remain so until 2023. Synergy forecasts strong growth across all SaaS segments and all geographic regions,” the company wrote in its report.

Salesforce is the only one of the top five that was actually born in the cloud. Adobe, an early desktop software company, switched to cloud in 2013. Microsoft, of course, has been a desktop stalwart for many years before embracing the cloud over the last decade. SAP and Oracle are traditional enterprise software companies, born long before the cloud was even a concept, that began transitioning when the market began shifting.

Getting to a billion

Yet in spite of being late to the game, these numbers show that the market is still dominated by the old guard enterprise software companies and how difficult it is to achieve market dominance for companies born in the cloud. Salesforce emerged 20 years ago as an early cloud adherent, but of all of the enterprise SaaS companies that were started this century only ServiceNow and WorkDay show up in the Synergy list lumped in “the next 10.”

That’s not to say there aren’t SaaS companies making some serious money, just not quite as much as the top players to this point. Jason Lemkin, CEO and founder at SaaStr, a company that invests in and supports enterprise SaaS companies, says a lot of companies are close to that $1 billion goal than you might think, and he’s optimistic that we are going to see more.

“We will have at least 100 companies top $1 billion in ARR, probably many more. It is just math. Almost everyone IPO’ing [SaaS company] has 120-140% revenue retention. That will compound $100 million or $200 million to $1 billion. The only question is when,” he told TechCrunch.

SaaS revenue numbers by company

Chart courtesy of SaasStr

He adds that annualized numbers are very close behind ARR numbers and it won’t take long to catch up. Yet as we have seen with some of the companies on this list, it’s still not easy to get there.

It’s hard to develop a billion dollar SaaS company, and it takes time and patience, and perhaps some strategic acquisitions to get there, but the market trajectory continues to move upward. It will likely only grow stronger as more companies move to software in the cloud, and that bodes well for many of the players in this market, even those that didn’t show up on Synergy’s chart.


We’re talking Kubernetes at TC Sessions: Enterprise with Google’s Aparna Sinha and VMware’s Craig McLuckie

Over the past five years, Kubernetes has grown from a project inside of Google to an open source powerhouse with an ecosystem of products and services, attracting billions of dollars in venture investment. In fact, we’ve already seen some successful exits, including one from one of our panelists.

On September 5th at TC Sessions: Enterprise, we’re going to be discussing the rise of Kubernetes with two industry veterans. For starters we have Aparna Sinha, director of product management for Kubernetes and the newly announced Anthos product. Sinha was in charge of several early Kubernetes releases and has worked on the Kubernetes team at Google since 2016. Prior to joining Google, she had 15 years experience in enterprise software settings.

Craig McLuckie will also be joining the conversation. He’s one of the original developers of Kubernetes at Google. He went on to found his own Kubernetes startup, Heptio, with Joe Beda, another Google Kubernetes alum. They sold the company to VMware last year for $505 million after raising $33.5 million, according to Crunchbase data.

The two bring a vast reservoir of knowledge and will be discussing the history of Kubernetes, why Google decided to open source it and how it came to grow so quickly. Two other Kubernetes luminaries will be joining them. We’ll have more about them in another post soon.

Kubernetes is a container orchestration engine. Instead of developing large monolithic applications that sit on virtual machines, containers run a small part of the application. As the components get smaller, it requires an orchestration layer to deliver the containers when needed and make them go away when they are not longer required. Kubernetes acts as the orchestra leader.

As Kubernetes, containerization and the cloud-native ethos it encompasses has grown, it has helped drive the enterprise shift to the cloud in general. If you can write your code once, and use it in the cloud or on prem, it means you don’t have to manage applications using different tool sets and that has had broad appeal for enterprises making the shift to the cloud.

TC Sessions: Enterprise (September 5 at San Francisco’s Yerba Buena Center) will take on the big challenges and promise facing enterprise companies today. TechCrunch’s editors will bring to the stage founders and leaders from established and emerging companies to address rising questions, like the promised revolution from machine learning and AI, intelligent marketing automation and the inevitability of the cloud, as well as the outer reaches of technology, like quantum computing and blockchain.

Tickets are now available for purchase on our website at the early-bird rate of $395; student tickets are just $75.

Student tickets are just $75 – grab them here.

We have a limited number of Startup Demo Packages available for $2,000, which includes four tickets to attend the event.

For each ticket purchased for TC Sessions: Enterprise, you will also be registered for a complimentary Expo Only pass to TechCrunch Disrupt SF on October 2-4.


Percona Live 2019’s Top 10 Most Attended Talks

Percona Live 2019 Most Attended Talks

We’re counting down the top 10 most attended talks at the Percona Live Open Source Database Conference 2019! For those of you who attended, chances are that some of you were at a few of these talks.  Percona Live conferences provide the open source database community with an opportunity to discover and discuss the latest open source trends, technologies, and innovations. The conference includes the best and brightest innovators and influencers in the open source database industry.

10. InnoDB Management and Scalability Improvements in MySQL 8.0 – Sunny Bains (Oracle)

Sunny Bains (Oracle) discusses improvements in MySQL 8 like scalability and InnoDB Management. Oracle’s MySQL 8.0 is a major release of new features and capabilities, including a new data dictionary, hosted in InnoDB, new REDO logs design, new UNDO logs, a new scheduler, descending indexes, and much more! Learn all about the changes in InnoDB delivered with MySQL 8.0 and how they affect the performance and the manageability of your database!

9. MySQL Group Replication: The Magic Explained v2 – Frédéric Descamps (Oracle)

Frédéric Descamps (Oracle) explains how MySQL Group Replication replication works. This is a theoretical talk in which he explains in detail what replication is and how it works, what certification is and how it’s done. Also, what is XCOM and GCS.

8. Using Ansible to Manage MySQL at DigitalOcean – Ben Mildren, Andrew Moore, & Dan Kowalewski (DigitalOcean)

Ben Mildren, Andrew Moore, & Dan Kowalewski (DigitalOcean) discuss how they use Ansible to manage the internal MySQL services at DigitalOcean, where this has worked well for them, as well as some of the issues they have experienced along the way. They’ll dive into how we use Ansible to manage MySQL, ProxySQL & Orchestrator and other related technologies in their environment and discuss topics such as static vs dynamic config management, Ansible performance tuning & anti-patterns, as well as testing strategies.

7. From Scheduled Downtime to Self-Healing in Less Than a Year – Karoly Nagy (Salesforce)

Karoly Nagy (Salesforce) discusses scheduled downtime to self-healing and how you can achieve this in less than a year. Infrastructure automation is not easy, especially for stateful services like MySQL (or any other database for that matter). It goes way beyond the capabilities of Ansible, Chef, SaltStack or other similar tools. In this session, Karoly will show you how he went from fully manual operations to a self-healing system in less than a year at Salesforce.

6. New Features in ProxySQL 2.0 – René Cannaò & Nick Vyzas (ProxySQL)

René Cannaò & Nick Vyzas (ProxySQL) discuss new features in ProxySQL 2.0. ProxySQL, the high performance, high availability, protocol-aware proxy for MySQL is now GA in version 2.0. This version introduces several new features, like causal reads using GTID, better support for AWS Aurora, native support for Galera Cluster, LDAP authentication and SSL for client connections.

5. Vitess: Running Sharded MySQL on Kubernetes – Sugu Sougoumarane & Dan Kozlowski (PlanetScale)

Sugu Sougoumarane & Dan Kozlowski (PlanetScale) discuss how to shard MySQL on Kubernetes in Vitess. Vitess has continued to evolve into a massively scalable sharded solution for the cloud. It’s is now used for storing core business data for companies like Slack, Square, JD.com, and many others. This session will cover the high-level features of Vitess with a focus on what makes it cloud-native.

4. Databases at Scale, at Square – Emily Slocombe (Square)

Emily Slocombe (Square) discusses databases at scale. At Square, they operate thousands of database instances to power a financial network, from payments to payroll. In a word: money. “Mission-critical” isn’t critical enough. Come learn how they operate MySQL and Redis with billions of dollars at stake. They’ll look at everything: configuration, management, monitoring, tooling, security, high-availability, replication and more.

3. MySQL Performance Optimization and Troubleshooting with Percona Monitoring and Management – Peter Zaitsev (Percona)

Peter Zaitsev (Percona) will discuss how you can optimize and troubleshoot MySQL performance and demonstrate how Percona Monitoring and Management (PMM) enables you to solve these challenges using free and open source software. We will look at specific, common MySQL problems and review the essential components in PMM that allow you to diagnose and resolve them.

2. New Features in MySQL 8.0 Replication – Luís Soares (Oracle)

Luís Soares (Oracle) highlights the new replication features in MySQL 8.0. Those that were released pre and post-GA. Come and learn, directly from the engineers, how the new features help you operate, sustain, and extend your MySQL Replication infrastructure.

1. The MySQL Query Optimizer Explained Through Optimizer Trace – Øystein Grøvlen (Alibaba Cloud)

Øystein Grøvlen (Alibaba Cloud) introduces you to the inner workings of the MySQL Query Optimizer by showing you examples with Optimizer Trace.  Øystein will cover the main phases of the MySQL optimizer and its optimization strategies, including query transformations, data access strategies, the range optimizer, the join optimizer, and subquery optimization. They will also show how optimizer trace gives you insight into the cost model and how the optimizer does cost estimations.

Thanks to all sponsors, presenters, and attendees for a successful Percona Live Open Source Database Conference 2019! We look forward to seeing you all next year!


Fellow raises $6.5M to help make managers better at leading teams and people

Managing people is perhaps the most challenging thing most people will have to learn in the course of their professional lives – especially because there’s no one ‘right’ way to do it. But Ottawa-based startup Fellow is hoping to ease the learning curve for new managers, and improve and reinforce the habits of experienced ones with their new people management platform software.

Fellow has raised $6.5 million in seed funding, from investors including Inovia Capital, Felicis Ventures, Garage Capital and a number of angels. The funding announcement comes alongside the announcement of their first customers, including Shopify (disclosure: I worked at Shopify when Fellow was implemented and was an early tester of this product, which is why I can can actually speak to how it works for users).

The Fellow platform is essentially a way to help team leads interact with their reports, and vice versa. It’s a feedback tool that you can use to collect insight on your team from across the company; it includes meeting supplemental suggestions and templates for one-on-ones, and even provides helpful suggestions like recommending you have a one-on-one when you haven’t in a while; and it all lives in the cloud, with integrations for other key workplace software like Slack that help it integrate with your existing flow.

Fellow co-founder and CEO Aydin Mirzaee and his co-founding team have previous experience building companies: They founded Fluidware, a survey software company, in 2008 and then sold it to SurveyMonkey in 2014. In growing the team to over 100 people, Mirzaee says they realized where there were gaps, both in his leadership team’s knowledge and in available solutions on the market.

“Starting the last company, we were in our early 20s, and like the way that we used to learn different practices was by using software, like if you use the Salesforce, and you know nothing about sales, you’ll learn some things about sales,” Mirzaee told me in an interview. “If you don’t know about marketing, use Marketo, and you’ll learn some things about marketing. And you know, from our perspective, as soon as we started actually having some traction and customers and then hired some people, we just got thrown into it. So it was ‘Okay, now, I guess we’re managers.’ And then eventually we became managers of managers.”

Fellow Team Photo 2019

Mirzaee and his team then wondered why a tool like Salesforce or Marketo didn’t exist for management. “Why is it that when you get promoted to become a manager, there isn’t an equivalent tool to help you with that?” he said.

Concept in hand, Fellow set out to build its software, and what it came up with is a smartly designed, user-friendly platform that is accessible to anyone regardless of technical expertise or experience with management practice and training. I can attest to this first-hand, since I was a first-time manager using Fellow to lead a team during my time at Shopify – part of the beta testing process that helped develop the product into something that’s ready for broader release. I was not alone in my relative lack of management knowledge, Mirzaee said, and that’s part of why they saw a clear need for this product.

“The more we did research, the more we figured out that obviously, managers are really important,” he explained. “70% of customer engagements are due to managers, for instance. And when people leave companies, they tend to leave the manager, not the company. The more we dug into it the more it was clear that there truly was this management problem –  management crisis almost, and that nobody really had built a great tool for managers and their teams like.”

Fellow’s tool is flexible enough to work with specific management methodologies like setting SMART goals or OKRs for team members, and managers can use pre-set templates or build their own for things like setting meeting talking points, or gathering feedback from the colleagues of their reports.

Right now, Fellow is live with a number of clients including Shoify, Vidyard, Tulip, North and more, and it’s adding new clients who sign up on a case-by-case basis, but increasing the pace at which it onboard new customers. Mirzaee explained that it hopes to open sign ups entirely later this year.


Fungible raises $200 million led by SoftBank Vision Fund to help companies handle increasingly massive amounts of data

Fungible, a startup that wants to help data centers cope with the increasingly massive amounts of data produced by new technologies, has raised a $200 million Series C led by SoftBank Vision Fund, with participation from Norwest Venture Partners and its existing investors. As part of the round, SoftBank Investment Advisers senior managing partner Deep Nishar will join Fungible’s board of directors.

Founded in 2015, Fungible now counts about 200 employees and has raised more than $300 million in total funding. Its other investors include Battery Ventures, Mayfield Fund, Redline Capital and Walden Riverwood Ventures. Its new capital will be used to speed up product development. The company’s founders, CEO Pradeep Sindhu and Bertrand Serlet, say Fungible will release more information later this year about when its data processing units will be available and their on-boarding process, which they say will not require clients to change their existing applications, networking or server design.

Sindu previously founded Juniper Networks, where he held roles as chief scientist and CEO. Serlet was senior vice president of software engineering at Apple before leaving in 2011 and founding Upthere, a storage startup that was acquired by Western Digital in 2017. Sindu and Serlet describe Fungible’s objective as pivoting data centers from a “compute-centric” model to a data-centric one. While the company is often asked if they consider Intel and Nvidia competitors, they say Fungible Data Processing Units (DPU) complement tech, including central and graphics processing units, from other chip makers.

Sindhu describes Fungible’s DPUs as a new building block in data center infrastructure, allowing them to handle larger amounts of data more efficiently and also potentially enabling new kinds of applications. Its DPUs are fully programmable and connect with standard IPs over Ethernet local area networks and local buses, like the PCI Express, that in turn connect to CPUs, GPUs and storage. Placed between the two, the DPUs act like a “super-charged data traffic controller,” performing computations offloaded by the CPUs and GPUs, as well as converting the IP connection into high-speed data center fabric.

This better prepares data centers for the enormous amounts of data generated by new technology, including self-driving cars, and industries such as personalized healthcare, financial services, cloud gaming, agriculture, call centers and manufacturing, says Sindu.

In a press statement, Nishar said “As the global data explosion and AI revolution unfold, global computing, storage and networking infrastructure are undergoing a fundamental transformation. Fungible’s products enable data centers to leverage their existing hardware infrastructure and benefit from these new technology paradigms. We look forward to partnering with the company’s visionary and accomplished management team as they power the next generation of data centers.”


Cathay Innovation leads Laiye’s $35M round to bet on Chinese enterprise IT

For many years, the boom and bust of China’s tech landscape have centered around consumer-facing products. As this space gets filled by Baidu, Alibaba, Tencent, and more recently Didi Chuxing, Meituan Dianping, and ByteDance, entrepreneurs and investors are shifting attention to business applications.

One startup making waves in China’s enterprise software market is four-year-old Laiye, which just raised a $35 million Series B round led by cross-border venture capital firm Cathay Innovation. Existing backers Wu Capital, a family fund, and Lightspeed China Partners, whose founding partner James Mi has been investing in every round of Laiye since Pre-A, also participated in this Series B.

The deal came on the heels of Laiye’s merger with Chinese company Awesome Technology, a team that’s spent the last 18 years developing Robotic Process Automation, a term for technology that lets organizations offload repetitive tasks like customer service onto machines. With this marriage, Laiye officially launched its RPA product UiBot to compete in the nascent and fast-growing market for streamlining workflow.

“There was a wave of B2C [business-to-consumer] in China, and now we believe enterprise software is about to grow rapidly,” Denis Barrier, co-founder and chief executive officer of Cathay Innovation, told TechCrunch over a phone interview.

Since launching in January, UiBot has collected some 300,000 downloads and 6,000 registered enterprise users. Its clients include major names such as Nike, Walmart, Wyeth, China Mobile, Ctrip and more.

Guanchun Wang, chairman and CEO of Laiye, believes there are synergies between AI-enabled chatbots and RPA solutions, as the combination allows business clients “to build bots with both brains and hands so as to significantly improve operational efficiency and reduce labor costs,” he said.

When it comes to market size, Barrier believes RPA in China will be a new area of growth. For one, Chinese enterprises, with a shorter history than those found in developed economies, are less hampered by legacy systems, which makes it “faster and easier to set up new corporate software,” the investor observed. There’s also a lot more data being produced in China given the population of organizations, which could give Chinese RPA a competitive advantage.

“You need data to train the machine. The more data you have, the better your algorithms become provided you also have the right data scientists as in China,” Barrier added.

However, the investor warned that the exact timing of RPA adoption by people and customers is always not certain, even though the product is ready.

Laiye said it will use the proceeds to recruit talents for research and development as well as sales of its RPA products. The startup will also work on growing its AI capabilities beyond natural language processing, deep learning, and reinforcement learning, in addition to accelerating commercialization of its robotic solutions across industries.




InnoDB ALTER TABLE ADD INDEXIn my previous blog post, I explained the internals of the sorted index build process. The blog ended with saying “there is one disadvantage.”

Beginning in MySQL 5.6, many DDLs including ALTER TABLE ADD INDEX became “ONLINE”. Meaning, when the ALTER is in progress, there can be concurrent SELECTS and DMLs. See the MySQL documentation for online DDL. From the documentation, we can see that ALTER TABLE ADD INDEX DDL permits concurrent DML.

The main disadvantage with Sorted Index Builds introduced in 5.7 is the reduced insert performance when ALTER is in progress. In this blog, we specifically talk about single thread insert performance on a table with ALTER ADD INDEX in progress.

If the table is huge, let’s say around 600 million rows or more, the inserts can even crash the server. This is especially true for ALTERs that run for hours and the concurrent insert waits for more than 600 seconds. InnoDB’s monitor thread crashes the server, stating that the INSERT waited for latch more than 600 seconds. It is reported as MySQL Bug#82940

Is it fixed?

The problem has existed since 5.7 GA and it is fixed in the latest release of Percona Server for MySQL 5.7.26-29  and 8.0.15-6 as part of PS-3410 bug fix. The number of inserts completed depends on whether the table is compressed or uncompressed, as well as the page size.

Percona’s fix is provided to upstream (Oracle MySQL) https://github.com/mysql/mysql-server/pull/268 but has yet to be included. We hope Oracle will include the fix in their next 5.7 release for the benefit of the MySQL community.

If you cannot upgrade to PS-5.7.26, one reasonable workaround would be to use pt-online-schema-change. With this tool, ensure that you have disk space at least equal to the original tablespace size.

How much is the improvement?

The % of improvement depends on the test scenario, machine configuration, etc. See details below.

For uncompressed tables, compared to 5.7.25 (baseline), with the fix version (5.7.26), 58% more inserts finished when ALTER ADD INDEX is running.

For compressed tables, 322% more inserts finished when ALTER ADD INDEX is running.

How does it compare to 5.6?

After the fix, for uncompressed tables, the number of inserts (from a single connection) completed during ALTER ADD INDEX is the same as 5.6.

For compressed tables, the number of inserts completed with 5.6.44 is 43% more than 5.7.26 (which has a fix). This is a bit surprising, and more analysis has to be done to find the reason. A topic for another day.

The problem from a design perspective

As part of sorted index builds, on the index being built, index->lock is acquired in X (exclusive) mode. This lock is held for the entire duration of the sorted index build. Yes, you read it right, for the entire duration. See PS-3410 for complete details.

Concurrent inserts will be able to see that there is a ‘new index’ being built. For such indexes, inserts go into Online ALTER logs, which are later executed at the end of ALTER. As part of this, INSERT tries to acquire index->lock in S (shared) mode to see if the index is in an online or aborted state.

Since the sorted index build process holds index->lock in X mode for the entire duration, concurrent insert waits for this latch. If the index is huge, the wait by insert thread crosses 600 seconds, and it will crash the server.


The fix is rather simple. Sorted index builds do not need to acquire index->lock in X mode. At this stage, there are no concurrent reads on this uncommitted index. Concurrent inserts do not interfere with the sorted index build. They go to online ALTER logs. So it is safe to not acquire the index->lock of the index being built.

Test Case

The following MTR test case is written to show the number of inserts that are concurrently executed while ALTER is running. Note that there is only one connection that does the inserts.

The test is run with innodb_buffer_pool_size = 1G for all versions. Two versions of the table are used. One with regular 16K page size and the other a compressed table with 4K page size.

The data directory is stored in RAM for all tests. You can save the below file (for example as mysql-test/t/alter_insert_concurrency.test) and run the MTR test case as:

./mtr --mem main.alter_insert_concurrency --mysqld=--innodb_buffer_pool_size=1073741824

The test inserts 10 million rows to the table and does CREATE INDEX (same as ALTER TABLE t1 ADD INDEX) and in another connection, INSERTS are executed one by one until ALTER finishes.

--source include/have_innodb.inc
--source include/count_sessions.inc
connect (con1,localhost,root,,);
class INT,
id INT,
title VARCHAR(100),
title2 VARCHAR(100)
CREATE PROCEDURE populate_t1()
WHILE (i <= 1000000) DO
INSERT INTO t1 VALUES (i, i, uuid(), uuid());
SET i = i + 1;
CREATE PROCEDURE conc_insert_t1()
IF @val > 0 THEN
WHILE (@val > 0) DO
INSERT INTO t1 VALUES (i, i, uuid(), uuid());
SET i = i + 1;
SELECT concat('Total number of inserts is ', i);
CALL populate_t1();
--connection con1
--send CREATE INDEX idx_title ON t1(title, title2);
--connection default
--sleep 1
--send CALL conc_insert_t1();
--connection con1
--connection default
--disconnect con1
DROP PROCEDURE populate_t1;
DROP PROCEDURE conc_insert_t1;
--source include/wait_until_count_sessions.inc


compressed 4k           : number of concurrent inserts (Avg of 6 runs)
==============            ============================
PS 5.7.25 (and earlier) : 2315
PS 5.7.26 (fix version) : 9785.66 (322% improvement compared to 5.7.25) (43% worse compared to 5.6)
PS 5.6                  : 17341
16K page size
PS 5.7.25 (and earlier) : 3007
PS 5.7.26 (fix version) : 4768.33 (58.5% improvement compared to 5.7.25) (3.4% worse compared to 5.6)
PS 5.6                  : 4939


Amperity update gives customers more control over Customer Data Platform

The Customer Data Platform (CDP) has certainly been getting a lot of attention in marketing software circles over the last year as big dawgs like Salesforce and Adobe enter the fray, but Amperity, a Seattle-based startup, has been building a CDP solution since it launched in 2016, and today it announced some updates to give customers more control over the platform.

Chris Jones, chief product officer at Amperity, says this is an important step for the startup. “If you think about the evolution of our company, we started with an idea that turned into a [Marketing Data Platform], which was the engine that powered all of that, but that engine was largely operated by our delivery team. We’re now putting the power of that engine into the customers’ hands and giving them the full access to that,” Jones explained.

That is giving customers — which include Alaska Airlines, Nordstrom and The Gap — the power to control how the software works in the context of their companies, rather than using a black box approach where you have to use the software as delivered. He says that customers want the ability to start using the system to gain insights on their own.

One of the primary pieces in the newest version of Amperity to allow them to do that is Stitch, a tool that lets users pull together all of the interactions from a customer in a single view —  ingesting the data, sorting, deduplicating it and delivering a list of all the interactions a brand has had with a given customer. From there, they can use the new Customer 360 visualization to get a more graphical view of the data.

Amperity Stitch 2019

Amperity Stitch Screenshot: Amperity.

Jones says companies can use this data to help different groups within a company, whether marketing, sales or service, understand the customer better before or during an interaction. For example, a marketer can segment the data in a very granular way to find all of the regular customers who aren’t part of the company loyalty program, and deliver them an email listing all of the benefits of joining.

Amperity launched in 2016, and has raised $37 million across two rounds. Its most recent funding came in 2017, a $28 million investment led by Tiger Global Management, according to Crunchbase data.


Upcoming Webinar 6/27: Beyond Relational Databases – A Look Into MongoDB, Redis, and ClickHouse

relational databases

Relational DatabasesPlease join Percona’s Principal Support Engineer Marcos Albe as he presents “Beyond Relational Databases: A Look Into MongoDB, Redis, and ClickHouse” on Thursday, June 27th, 2019 at 12:00 PM PDT (UTC-7).

Register Now

We all use and love relational databases… until we use them for purposes for which they are not a good fit: queues, caches, catalogs, unstructured data, counters, and many other use cases could be solved with relational databases, but are better solved with other alternatives.

In this talk, we’ll review the goals, pros and cons, and good and bad use cases of these alternative paradigms by looking at some modern open source implementations.

By the end of this talk, the audience will have learned the basics of three database paradigms (document, key-value, and columnar store) and will know when it’s appropriate to opt for one of these or when to favor relational databases and avoid falling into buzzword temptations.


Percona XtraDB Cluster 5.7.26-31.37 Is Now Available

Percona XtraDB Cluster 5.7

Percona XtraDB Cluster 5.7

Percona is glad to announce the release of Percona XtraDB Cluster 5.7.26-31.37 on June 26, 2019. Binaries are available from the downloads section or from our software repositories.

Percona XtraDB Cluster 5.7.26-31.37 is now the current release, based on the following:

All Percona software is open-source and free.

Bugs Fixed

  • PXC-2480: In some cases, Percona XtraDB Cluster could not replicate CURRENT_USER() used in the ALTER statement. USER() and CURRENT_USER() are no longer allowed in any ALTER statement since they fail when replicated.
  • PXC-2487: The case when a DDL or DML action was in progress from one client and the provider was updated
    from another client could result in a race condition.
  • PXC-2490: Percona XtraDB Cluster could crash when binlog_space_limit was set to a value other than zero during wsrep_recover mode.
  • PXC-2491: SST could fail if the donor had encrypted undo logs.
  • PXC-2497: The user can set the preferred donor by setting the wsrep_sst_donor variable. An IP address is not valid as the value of this variable. If the user still used an IP address, an error message was produced that did not provide sufficient information. The error message has been improved to suggest that the user check the value of the wsrep_sst_donor for an IP address.
  • PXC-2537: Nodes could crash after an attempt to set a password using mysqladmin

Other bugs fixedPXC-2276PXC-2292PXC-2476,  PXC-2560

Help us improve our software quality by reporting any bugs you encounter using our bug tracking system. As always, thanks for your continued support of Percona!

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