Timescale Advances Best-In-Class Price Performance for Developers With Launch of New Object Storage Layer on Amazon S3
Timescale the creators of Timescale Cloud, the cloud-native PostgreSQL for time series, analytics, and events — announced the private beta launch of a consumption-based, low-cost object storage layer built on Amazon S3. Timescale Cloud customers can now store an infinite amount of data to power their applications, paying only for what they store.
Timescale’s new capabilities expand the boundaries of traditional managed databases with a novel cloud-native architecture designed to save developers money and time, incorporating elements typically associated with data warehouses and data lakes, enabling PostgreSQL developers to grow their data effortlessly for a fraction of the price of traditional storage.
Recommended AI: Top 10 Countries and Cities by Number of CCTV Cameras
Rather than operating an external system for data archiving alongside a time-series database which often creates data silos and operational overhead, developers can now simply work with a single table where data is transparently tiered across different storage systems while retaining the ability to query that data via standard SQL.
“Since starting Timescale in 2017, we’ve continually provided the full PostgreSQL experience, which developers trust and love, and have now expanded it further for a cloud-native future,” said Mike Freedman, Timescale’s Co-founder and CTO. “These innovative data tiering capabilities seamlessly combine the strengths of an object store with our cloud database built on PostgreSQL. This makes it easier and cheaper for developers to operate data-intensive applications in AWS.”
Recommended AI: How is Artificial Intelligence (AI) Changing the Future of Architecture?
Timescale built new database internal capabilities and external subsystems to give application developers access to an object store from within a PostgreSQL database in Timescale Cloud. The result is that time-series tables, called hypertables, can now stretch across standard disk storage (in Amazon EBS) and object storage (in Amazon S3), with data formats that are optimized for each layer. Query optimizations ensure that data is fetched from both disk and object storage for a single SQL query, abstracting away complexity from the PostgreSQL developer.
In addition to cost-efficient data tiering, future enhancements to Timescale’s newly released object store will seek to enable easier data sharing between fleets of databases, faster transfer of data into new deployments, and smoother migration of data from external data warehouses to Timescale Cloud.
Recommended AI: AMD Expands Data Center Solutions Capabilities with Acquisition of Pensando
[To share your insights with us, please write to sghosh@martechseries.com]
Comments are closed.