Materialize, the streaming SQL database company, today launched the open beta for Materialize Cloud, which offers the first standard SQL interface for streaming data. Materialize Cloud makes it simple for any business to understand streaming data, answer complex questions and build intelligent applications without needing specialized skills.
Traditionally, making use of streaming data has required heavy investments in engineering resources that have made the move to real-time infrastructure off limits for many organizations. Materialize Cloud now makes it easy for companies of any size to incorporate streaming data into their applications. Unlike competing products that require customers to learn new languages, Materialize Cloud is based on industry-standard SQL, and is easy to set up, scale and begin using “out of the box.”
“The ability to use real-time data for insights and value will determine which companies lead their industries in the years ahead,” said Arjun Narayan, co-founder and CEO of Materialize. “For Materialize, the main motivation behind the product is streaming data. Our team has been studying this topic for decades and we are especially proficient at providing streaming services to our customers.”
The Materialize team includes engineers who were early employees of Cockroach Labs, Dropbox and YouTube. Frank McSherry, co-founder and chief scientist of Materialize, led the research behind Timely Dataflow and Differential Dataflow, which serve as the basis of Materialize.
Key features of Materialize Cloud include:
- Managed database-as-a-service, making it easy to set up and operate a streaming database and automate administration tasks.
- Managed cloud service inclusive of deployment, security, maintenance, and upgrades of Materialize instances.
- Operational visibility and insight with support for endpoint integrations with monitoring tools, as well as the ability to troubleshoot database and SQL queries.
- Millisecond-level latency, a SQL-first architecture, and the ability to handle real-time complex JOINS.
- Integration with various sources of data including event streaming platforms like Apache Kafka and Amazon Kinesis, CDC, historical sources like S3 and local files, data lakes and Postgres databases.
- Out-of-the-box support for dbt, extending its tremendous support among analysts from batch data to streaming data”
- Enterprise-grade security, with all data secured in dedicated networks and machines, with support for encryption in-transit and at-rest via industry-leading security (TLS 1.2, EBS-encryption, and SOC2 certification).
Early customers are using Materialize for real-time data visualization, financial modeling, and to provide advanced intelligence capabilities for various SaaS applications in martech, logistics, and enterprise resource planning. Over the last six months Materialize has attracted a wide range of customers, from companies like Drizly, an eCommerce platform for buying beer, wine and spirits to Kepler Cheuvreux, an independent Paris-based financial services company.
“Working with Materialize has been an incredibly seamless process as we can continue to write real-time SQL, exactly the same way as we already are in Snowflake with batch, so it was a much lower barrier to entry,” said Emily Hawkins, Data Infrastructure Lead, Drizly. “It was also a huge plus for us that we could continue using dbt within the real-time platform to help us address our online cart conversion challenges where customers can be reminded of a pending purchase in the span of minutes versus hours.”
Materialize Cloud is available now in open beta and Materialize is offering a free 30-day trial. For more information or to sign up, visit http://materialize.com/materialize-cloud/.
About Materialize
Materialize is the streaming database company that makes it easy for any developer or analyst to understand real-time data, answer complex questions and build intelligent applications. Based in New York City, the Materialize team includes engineers who were early employees of Cockroach Labs, PayPal, Dropbox and YouTube.