Version 2.26.916: Triumphant Thilde is now available! This release brings significant performance improvements, new python numpy/pandas and torch support, a brand new Node.js Typescript package, enhanced support for data compression, including zlib-ng, lz4, and snappy. Enhanced support for mmap/mlock, ipcv, Linux HugePages, and more. Add in database partitioning/sharding, slicing, replication and ClockworkDB is ready for your multi-petabyte databases today. Explore the new capabilities and supercharge your data analysis with ClockWorkDB.
25 years in the making, developed to power some of the world's largest financial data warehouses,
accelerate your time series, vector, extensible workflows with our high-performance, developer-first platform.
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Research independent benchmarks! (Coming soon...)
Curated Time Tech's ClockWorkDB is built with developers in mind. Built for the cloud, on-prem, or on your workstation. ClockWorkDB's simple configuration and zero maintenance let's the team get to doing what they do best. Develop.
Regardless your chosen development languange, OS, or Persistence backend, ClockWorkDB can likely meet your needs.
Whether an RDBMS, NoSQL, or proprietary database like KDB, ClockWorkDB provides a consistent API for TimeSeries and Columnar data, for native types, structures, JSON, XML, Blobs and beyond.
QuantumChest and WarpDrive+ storage engines provide the ultimate in performance and extended features including HA, Replication, Petabyte+ storage, slicing and sharding.
Purpose-built architecture optimized for native data types, stuctures, JSON, XML, Blobs, and more. Inovative calendaring reduces dates and times to integers for constant time indexing.
Native support for popular languages with dedicated client libraries.
auto engine = engine::Instance();
auto session = engine.get_session("data-repo");
auto connection = session->get_connection();
auto datastore = connection->get_datastore("market-data",
access_mode::read_write());
auto timeseries = datastore->get_time_series("nvda.close");
...
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