![]() Timeplus supports various data source connections such as Apache Kafka, Amazon S3 and Amazon Kinesis. Timeplus is not only a streaming SQL database, it provides end to end analytic functionalities. You can join a stream with other streams, or enrich them with data from CSV, S3 or databases. Common streaming windows are supported such as tumble, hopping, session. Each query in Timeplus can detect late events, and you can choose to drop or wait for them. As our company name implies, we are specialized to process real-time data. Timeplus provides unique solutions to analyze both real-time data and historical data. Timeplus has a high performance streaming SQL engine, leveraging vectorized data computing capability, streaming data is processed in super high efficiency with the modern parallel processing technology Instruction/Multiple Data (SIMD). Timeplus Native log also supports timestamp based seek and optimized time series data analytics scenarios. Combined with TDF, Timeplus Native Log provides high performance data ingestion, it can quickly prune data on disk and filter out data which is not required for streaming processing. ![]() To fully leverage the capability of TDF, Timeplus also designed a stream storage called Timeplus Native Log. Since it is in column format, data can be vectorized for high performance analytic computation. Timeplus has designed a column based data format called Timeplus Data Format (TDF), which supports blazing fast serialization and de-serialization. Timeplus is a fast and powerful real-time analytics platform.
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