Our results surprised even us - but even after testing with several different configurations, we found Amazon Timestream slow, expensive, and missing key database capabilities like backups, restores, updates, and deletes.
TimescaleDB, first launched in April 2017, is today the industry-leading relational database for time-series, open-source, engineered on top of PostgreSQL, and offered via download or as a fully-managed service on AWS, Azure, and GCP.
The TimescaleDB community has become the largest developer community for time-series data: tens of millions of downloads; over 500,000 active databases; organizations like AppDynamics, Bosch, Cisco, Comcast, Credit Suisse, DigitalOcean, Dow Chemical, Electronic Arts, Fujitsu, IBM, Microsoft, Rackspace, Schneider Electric, Samsung, Siemens, Uber, Walmart, Warner Music, WebEx, and thousands of others (all in addition to the PostgreSQL community and ecosystem).
And, given its roots, TimescaleDB supports everything in the PostgreSQL ecosystem, including tools like EXPLAIN that help pinpoint why queries are slow and identify ways to improve performance.
Materialize, the SQL streaming database startup built on top of the open source Timely Dataflow project, announced a $32 million Series B investment today led by Kleiner Perkins with participation from Lightspeed Ventures.
Further, he says the company is built using SQL because of its ubiquity, and the founders wanted to make sure that customers could access and make use of that data quickly without learning a new query language.
They would naturally get compared to Confluent, a streaming database built on top of the Apache Kafka open source streaming database project, but Narayan says his company uses straight SQL for querying, while Confluent uses its own flavor.
They currently have 20 employees with plans to double that number by the end of next year as they continue to build out the product.