VeloDB vs. Axibase Time Series Database

Axibase Time Series Database

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What is VeloDB?

VeloDB, powered by Apache Doris, is an innovative data warehouse tailored for swift analytics on extensive real-time data streams. It incorporates both push-based micro-batch and pull-based streaming data ingestion processes that occur in just seconds, along with a storage engine that supports real-time upserts, appends, and pre-aggregations, resulting in outstanding performance for serving real-time data and enabling dynamic interactive ad-hoc queries. VeloDB is versatile, handling not only structured data but also semi-structured formats, and it offers capabilities for both real-time analytics and batch processing, catering to diverse data needs. Additionally, it serves as a federated query engine, facilitating easy access to external data lakes and databases while integrating seamlessly with internal data sources. Designed with distribution in mind, the system guarantees linear scalability, allowing users to deploy it either on-premises or as a cloud service, which ensures flexible resource allocation according to workload requirements, whether through the separation or integration of storage and computation components. By capitalizing on the benefits of the open-source Apache Doris, VeloDB is compatible with the MySQL protocol and various functions, simplifying integration with a broad array of data tools and promoting flexibility and compatibility across a multitude of environments. This adaptability makes VeloDB an excellent choice for organizations looking to enhance their data analytics capabilities without compromising on performance or scalability.

What is Axibase Time Series Database?

An advanced parallel query engine enables efficient access to both time- and symbol-indexed data. It incorporates an upgraded SQL syntax that facilitates complex filtering and extensive aggregations. This innovative system merges diverse financial data types, including market quotes, trade transactions, snapshots, and reference information, into a unified database. Users can perform strategy backtesting with high-frequency datasets, engage in quantitative research, and analyze market microstructure dynamics. The platform offers in-depth transaction cost analysis alongside rollup reporting, which ensures a comprehensive understanding of trading activities. With integrated market surveillance features and anomaly detection tools, it enhances overall monitoring capabilities. It also has the capacity to break down opaque ETFs and ETNs while employing FAST, SBE, and proprietary protocols to boost performance. A straightforward text protocol simplifies usage, and both consolidated and direct data feeds are provided for seamless data ingestion. Additionally, built-in latency monitoring tools and extensive end-of-day data archives are part of the offering. The engine supports ETL processes from both institutional and retail financial data sources, and its parallel SQL engine comes with syntax extensions that allow for advanced filtering based on various parameters, such as trading sessions and auction stages. It further provides optimized calculations for OHLCV and VWAP metrics, enhancing analytical precision. An interactive SQL console with auto-completion features improves user interaction, while an API endpoint supports programmatic integration. Scheduled SQL reports can be generated with delivery options via email, file, or web, complemented by JDBC and ODBC drivers for wider accessibility.