Promscale Alternatives
Similar projects and alternatives to promscale
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TimescaleDB
An open-source time-series SQL database optimized for fast ingest and complex queries. Packaged as a PostgreSQL extension.
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SonarLint
Deliver Cleaner and Safer Code - Right in Your IDE of Choice!. SonarLint is a free and open source IDE extension that identifies and catches bugs and vulnerabilities as you code, directly in the IDE. Install from your favorite IDE marketplace today.
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thanos
Highly available Prometheus setup with long term storage capabilities. A CNCF Incubating project.
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tsbs
Time Series Benchmark Suite, a tool for comparing and evaluating databases for time series data
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VictoriaMetrics
VictoriaMetrics: fast, cost-effective monitoring solution and time series database
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Scout APM
Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.
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pmacct
pmacct is a small set of multi-purpose passive network monitoring tools [NetFlow IPFIX sFlow libpcap BGP BMP RPKI IGP Streaming Telemetry].
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timescale-analytics
Extension for more hyperfunctions, fully compatible with TimescaleDB and PostgreSQL 📈
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Logflare
Never get surprised by a logging bill again. Centralized structured logging for Cloudflare, Vercel, Elixir and Javascript.
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orioledb
OrioleDB – building a modern cloud-native storage engine (... and solving some PostgreSQL wicked problems) 🇺🇦
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tobs
tobs - The Observability Stack for Kubernetes. Easy install of a full observability stack into a k8s cluster with a CLI tool or Helm charts.
promscale reviews and mentions
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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
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Tools for Querying Logs with SQL
Promscale is a connector for Prometheus, one of the leading open-source monitoring solutions. Promscale is developed by Timescale, a time series database with full compatibility to Postgres. Since logs are time series events, Timescale developed Promscale to ingest events from Prometheus and make them available in SQL. You can install Promscale in numerous ways.
- New release Promscale
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Can Apache Druid replace Thanos? Can they complement themself?
In case it helps, Promscale (from Timescale) offers long-term storage for Prometheus data and supports both PromQL and SQL queries. Here's the project page: https://www.timescale.com/promscale/ and the repo is here https://github.com/timescale/promscale It also support OpenTelemetry tracing if that's of interest.
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Benchmarking: TimescaleDB vs. ClickHouse
At first, let's give the definition of `time series`. This is a series of (timestamp, value) pairs ordered by timestamp. The `value` may contain arbitrary data - a floating-point value, a text, a json, a data structure with many columns, etc. Each time series is uniquely identified by its name plus an optional set of {label="value"} labels. For example, temperature{city="London",country="UK"} or log_stream{host="foobar",datacenter="abc",app="nginx"}.
ClickHouse is perfectly optimized for storing and querying of such time series, including metrics. That's true that ClickHouse isn't optimized for handling millions of tiny inserts per second. It prefers infrequent batches with big number of rows per each batch. But this isn't the real problem in practice, because:
1) ClickHouse provides Buffer table engine for frequent inserts.
2) It is easy to create a special proxy app or library for data buffering before sending it to ClickHouse.
TimescaleDB provides Promscale [1] - a service, which allows using TimescaleDB as a storage backend for Prometheus. Unfortunately, it doesn't show outstanding performance comparing to Prometheus itself and to other remote storage solutions for Prometheus. Promscale requires more disk space, disk IO, CPU and RAM according to production tests [2], [3].
[1] https://github.com/timescale/promscale
[2] https://abiosgaming.com/press/high-cardinality-aggregations/
[3] https://valyala.medium.com/promscale-vs-victoriametrics-reso...
Full disclosure: I'm CTO at VictoriaMetrics - competing solution for TimescaleDB. VictoriaMetrics is built on top of architecture ideas from ClickHouse.
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Zabbix anything I should know?
Promscale + TimescaleDB
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A different and (often) better way to downsample your Prometheus metrics
(NB: Promscale team member)
Thanks for the positive feedback!
Is there anything in particular you are missing in Promscale to be used as a backend for multiple Prometheus instances?
We added support for multi-tenancy a couple of months ago (https://blog.timescale.com/blog/simplified-prometheus-monito...)
And thanks to a community contribution by 2nick on github Promscale can be integrated with Thanos :) (https://github.com/timescale/promscale/pull/664)
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Monitoring Operational Data with Prometheus and Grafana
TimescaleDB is a PostgreSQL extension that's designed to support time-series data and so makes a great home for long-term storage for Prometheus which it achieves with Promscale (an open-source project). We also just today launched support for tracing (OpenTelemetry) too.
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Thanos Integration with Prometheus
No. No you can’t store Prometheus metrics in Postgres out of the box AFAIK. You’d need to run a service that provides a remote write endpoint to proxy metrics into Postgres. There’s probably a few open source projects out there similar to: https://github.com/timescale/Promscale
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TimescaleDB Raises $40M
(Timescale engineer here). We believe so and we have customers using us for just that. We haven't created our own product for that yet (as we have for metrics -- Promscale) but it is an idea we are playing with. You may want to look at our Promscale design doc[1] for ideas on table layout.
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Monitoring my servers with Prometheus - Part 2
Since you're already using postgres, did you ever consider using the timescaleDB adaptor (now called promscale) for your backend to prometheus? I just configured a setup that uses promscale which gives me the power of SQL, plus you can still run queries running promQL. Grafana can be configured to connect to either prometheus or postgres (timescale). Best of both worlds for me.
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Prom-migrator: Migrate Prometheus Data
Or got right to the GitHub repo to get started.
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Long term storage for specific metrics
Any chance something like promscale or m3 could solve your problems?
Stats
timescale/promscale is an open source project licensed under Apache License 2.0 which is an OSI approved license.
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