Time Series Benchmark Suite, a tool for comparing and evaluating databases for time series data (by timescale)

Tsbs Alternatives

Similar projects and alternatives to tsbs

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better tsbs alternative or higher similarity.

tsbs reviews and mentions

Posts with mentions or reviews of tsbs. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-08-17.
  • Fuzz Testing Is the Best Thing to Happen to Our Application Tests
    3 projects | news.ycombinator.com | 17 Aug 2023
    1. correctness: from small units tests to relatively complex integrations tests. they typically populate a test database and query it via various interfaces, such as REST or the Postgres protocol. we use Azure Pipelines to execute them - testing in MacoOS, Linux (both Intel and ARM) and Windows.

    2. performance: we tend to use the TSBS project for most of our performance testing and profiling. fun fact: we actually had to patch it as the vanilla TSBS was a bottleneck in some tests. Sadly, the PR with the improvements is still not merged: https://github.com/timescale/tsbs/pull/186

  • MongoDB Time Series Benchmark and Review
    2 projects | dev.to | 22 Mar 2023
    As usual, we use the industry standard Time Series Benchmark Suite (TSBS) as the benchmark tool. Unfortunately, TSBS upstream does not support MongoDB time series collections.
  • Show HN: QuestDB with Python, Pandas and SQL in a Jupyter notebook – no install
    3 projects | news.ycombinator.com | 21 Feb 2023
    yes correct - although Clickhouse is more of an OLAP database. Timescale is built on top of Postgres, while QuestDB is built from scratch with Postgres wire compatibility. You can run benchmarks on https://github.com/timescale/tsbs
    3 projects | news.ycombinator.com | 21 Feb 2023
  • Streaming data storage
    2 projects | /r/dataengineering | 24 Jan 2023
    According their benchmark it is really fast.
  • Ingesting with CrateDB
    2 projects | dev.to | 18 Jan 2023
    We used the nodeIngestBench for all the benchmarking. It is a multi-process Node.js script that runs high-performance ingest benchmarks on CrateDB. It uses a data model that was adapted from Timescale’s Time Series Benchmark Suite (TSBS). One thing that we want to make clear is that nodeIngestBench is a write benchmark. The data structure that it creates is unsuitable for any performance-indicative reading tests because of its high cardinality (due to random data) and no partitioning.
  • 4Bn rows/sec query benchmark: Clickhouse vs QuestDB vs Timescale
    2 projects | dev.to | 23 Jun 2022
    In order to make the benchmark easily reproducible, we're going to use TSBS benchmark utilities to generate the data. We'll be using so-called IoT use case:
  • DeWitt Clause, or Can You Benchmark %DATABASE% and Get Away With It
    21 projects | dev.to | 2 Jun 2022
    Also, some open-source vendors collaboratively maintain benchmarking suites such as Time Series Benchmark Suite to help choose the best tools for particular workloads.
  • 4Bn rows/SEC query benchmark: ClickHouse vs. QuestDB vs. Timescale
    2 projects | news.ycombinator.com | 1 Jun 2022
    Last year we released QuestDB 6.0 and achieved an ingestion rate of 1.4 million rows per second (per server). We compared those results to popular open source databases [1] and explained how we dealt with out of order ingestion under the hood while keeping the underlying storage model read-friendly. Since then, we focused our efforts on making queries faster, in particular filter queries with WHERE clauses. To do so, we once again decided to make things from scratch and built a JIT (Just-in-Time) compiler for SQL filters, with tons of low-level optimisations such as SIMD. We then parallelized the query execution to improve the execution time even further. In this blog post, we first look at some benchmarks against Clickhouse and TimescaleDB, before digging deeper in how this all works within QuestDB's storage model. Once again, we use the Time Series Benchmark Suite (TSBS) [2], developed by TimescaleDB,: it is an open source and reproducible benchmark.

    We'd love to get your feedback!

    [1]: https://news.ycombinator.com/item?id=27411307

    [2] https://github.com/timescale/tsbs

    2 projects | news.ycombinator.com | 1 Jun 2022
    This table schema: https://github.com/timescale/tsbs/blob/bcc00137d72d889e6059e...

    ...seems like a quite odd way to store time-series in ClickHouse. If I understood that code correctly (and I am really not sure), they partition their data by some tag value (the first one in a list?) instead of time, which is what timescaledb afaik partitions by. Of course that query filtering by timerange is going to be slower than usual. Whether that makes sense depends on your usecase.

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    www.sonarlint.org | 3 Oct 2023
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Basic tsbs repo stats
12 days ago

timescale/tsbs is an open source project licensed under MIT License which is an OSI approved license.

The primary programming language of tsbs is Go.

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