Materialize’s ‘distributed database’ mobilizes streaming data with the simplicity of SQL
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New York-based Materialize today announced the early availability of the next generation of its distributed streaming database to help enterprises mobilize their real-time streaming data with SQL.
In the last few years, the value of real-time data has significantly increased. Companies want a way to act on information as soon as it is generated — to fuel their applications and people and stay ahead of the curve. However, in order to do that, they need to increase access and usage of real-time data, which continues to be a problem due to the complexity, cost and capabilities of existing tooling in the market. Essentially, batch-based tools may not deliver the latencies needed while those with streaming capabilities require specialization that increases complexity and cost.
Materialize handles streaming data with simplicity
Founded in 2019, Materialize addresses this gap with a fully-managed cloud database built on top of a powerful stream processor – Timely Dataflow – and wrapped in the SQL interface.
“This means that, for the first time, engineers can build on top of real-time, streaming data just using SQL. We don’t mean some subset of SQL or some custom query language, we mean ANSI SQL. And, even better, Materialize is wire-compatible with Postgres, which means that all of your team’s favorite data tools will work with Materialize, and over streaming data, out of the box,” Jessica Laughlin, chief of staff at Materialize, told VentureBeat.
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According to the company, the offering gives developers and data teams the power of streaming data with the same simplicity and low implementation cost as batch cloud data warehouses. They can use it to build customer-facing workflows, data applications or perform streaming analytics, leveraging integrations with powerful platforms like dbt.
In addition to reducing cost and complexity, Materialize also delivers strict serializability to eliminate stale and incorrect data; horizontal scalability – leveraging the underlying capabilities of Timely Dataflow – to let users handle large, fast-scaling workloads; and millisecond-level query latency on complex transformations, joins or aggregations.
“The main impact we’ve seen with customers is really centered around the overall ease-of-use of Materialize coupled with the strict-serializability – or correctness – of data,” Laughlin said.
“Despite spanning a large number of threads, processes and machines, Materialize presents to all users as if it handles each command one at a time. That means that users get to avoid all of the anomalies of eventual consistency, dual writes, and the other defects you didn’t know you need to know about. In fact, if two teams in your organization build out independent views over shared data, they will always remain consistent. If a third team wants to build on both of them, there is no reconciliation to perform; they just use the other teams’ views and see consistent, always up-to-date results. This consistency and sheer correctness of the data…is a first for companies building on real-time data.” she added.
Further, the offering also cuts the development time of real-time applications, enabling teams to deliver projects that previously took months in a matter of days or weeks.
What’s in the next generation?
With the launch of the new generation of Materialize, available as a cloud-native, fully-managed SaaS platform, the company is building out the product architecture to enable support for a host of new use cases. The new version includes capabilities like zero-downtime upgrades, separation of compute and elastic storage, multiway complex joins, active replication, seamless rescaling events and the ability to deploy new query plans without interrupting ongoing work.
“We’re seeing Materialize deployed globally and across a lot of really exciting use cases – particularly around real-time analytics, MLops, automation and alerting, as well as with segmentation and personalization. It’s been great to see the excitement of using SQL over real-time streaming data across a bunch of different verticals,” Laughlin said. She added that over 300 companies signed up for early access to the new version.
Materialize counts companies like Drizly, Unimarket, Sproutfi, Maqqie, Datalot and Kepler Cheuvreux among its customers and has already raised $100 million from leading venture capital firms including Kleiner Perkins, Lightspeed Venture Partners and Redpoint Ventures. Other companies in the same space are StarRocks, Yugabyte, Rockset, Clickhouse and Flink.
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