tobs
tsbs
tobs | tsbs | |
---|---|---|
1 | 76 | |
553 | 1,216 | |
0.7% | 1.2% | |
0.0 | 1.6 | |
3 days ago | 5 days ago | |
Shell | Go | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
tobs
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Timescale raises $110M Series C
Hi! So the team is over 100 at this point, but engineering effort is spread across multiple products at this point.
The core timescaledb repo [0] has 10-15 primary engineers (although we are aggressively hiring for database internal engineers), with a few others working on DB hyperfunctions and our function pipelining [1] in a separate extension [2]. I think generally the set of folks who contribute to low-level database internals in C is just smaller than other type of projects.
We also have our promscale product [3], which is our observability backend powered by SQL & TimescaleDB.
And then there is Timescale Cloud, which is obviously a large engineering effort (most of which does not happen in public repos).
And we are hiring. Fully remote & global.
https://www.timescale.com/careers
[0] https://github.com/timescale/timescaledb
[1] https://www.timescale.com/blog/function-pipelines-building-f...
[2] https://github.com/timescale/timescaledb-toolkit
[3] https://github.com/timescale/promscale ; https://github.com/timescale/tobs
tsbs
- tsbs: NEW Data - star count:1149.0
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Fuzz Testing Is the Best Thing to Happen to Our Application Tests
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
- tsbs: NEW Data - star count:1058.0
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MongoDB Time Series Benchmark and Review
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.
What are some alternatives?
orioledb - OrioleDB β building a modern cloud-native storage engine (... and solving some PostgreSQL wicked problems) Β πΊπ¦
QuestDB - An open source time-series database for fast ingest and SQL queries
kube-state-metrics - Add-on agent to generate and expose cluster-level metrics.
cql-proxy - A client-side CQL proxy/sidecar.
promscale - [DEPRECATED] Promscale is a unified metric and trace observability backend for Prometheus, Jaeger and OpenTelemetry built on PostgreSQL and TimescaleDB.
TimescaleDB - An open-source time-series SQL database optimized for fast ingest and complex queries. Packaged as a PostgreSQL extension.
grafana-dashboards-kubernetes - A set of modern Grafana dashboards for Kubernetes.
website-monitoring - Monitore your websites availability, http status code (current and history), certificate, redirects and more with Grafana and Prometheus blackbox exporter.
dbt-clickhouse - The Clickhouse plugin for dbt (data build tool)
timescale-analytics - Extension for more hyperfunctions, fully compatible with TimescaleDB and PostgreSQL π
Elasticsearch - Free and Open, Distributed, RESTful Search Engine