incubation-engineering
clickhouse-operator
incubation-engineering | clickhouse-operator | |
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18 | 5 | |
- | 1,739 | |
- | 2.4% | |
- | 9.8 | |
- | 3 days ago | |
Go | ||
- | Apache License 2.0 |
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.
incubation-engineering
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Why Postgres RDS didn't work for us
However if you really want to optimize data currently residing in Postgres for analytical workloads, as the original comment suggests - consider moving to a dedicated OLAP DB like ClickHouse.
See results from Gitlab benchmarking ClickHouse vs TimescaleDB: https://gitlab.com/gitlab-org/incubation-engineering/apm/apm...
Key findings:
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Automating Your Homelab with Proxmox, Cloud-init, Terraform, and Ansible
ansible: stage: configure image: alpine rules: - if: $ANSIBLE_SETUP_VM != "" && $ANSIBLE_SETUP_HOST != "" variables: ANSIBLE_HOST_KEY_CHECKING: "False" script: - apk add curl bash openssh python3 py3-pip - pip3 install ansible paramiko - ansible-galaxy collection install -r ansible/requirements.yml - curl --silent "https://gitlab.com/gitlab-org/incubation-engineering/mobile-devops/download-secure-files/-/raw/main/installer" | bash - mkdir /root/.ssh && cp .secure_files/ansible.priv /root/.ssh/id_rsa && chmod 600 /root/.ssh/id_rsa - ansible-playbook ansible/main.yml -i ansible/inventory --extra-vars vyos_host=$ANSIBLE_SETUP_VM --limit $ANSIBLE_SETUP_HOST,$ANSIBLE_SETUP_VM ```
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Float Compression 3: Filters
Interesting to match with the observations from the practice of using ClickHouse[1][2] for time series:
1. Reordering to SOA helps a lot - this is the whole point of column-oriented databases.
2. Specialized codecs like Gorilla[3], DoubleDelta[4], and FPC[5] lose to simply using ZSTD[6] compression in most cases, both in compression ratio and in performance.
3. Specialized time-series DBMS like InfluxDB or TimescaleDB lose to general-purpose relational OLAP DBMS like ClickHouse [7][8][9].
[1] https://clickhouse.com/blog/optimize-clickhouse-codecs-compr...
[2] https://github.com/ClickHouse/ClickHouse
[3] https://clickhouse.com/docs/en/sql-reference/statements/crea...
[4] https://clickhouse.com/docs/en/sql-reference/statements/crea...
[5] https://clickhouse.com/docs/en/sql-reference/statements/crea...
[6] https://github.com/facebook/zstd/
[7] https://arxiv.org/pdf/2204.09795.pdf "SciTS: A Benchmark for Time-Series Databases in Scientific Experiments and Industrial Internet of Things" (2022)
[8] https://gitlab.com/gitlab-org/incubation-engineering/apm/apm... https://gitlab.com/gitlab-org/incubation-engineering/apm/apm...
[9] https://www.sciencedirect.com/science/article/pii/S187705091...
- ClickHouse Cloud is now in Public Beta
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Dokter 1.4.0 released
Documentation of rules is now available: https://gitlab.com/gitlab-org/incubation-engineering/ai-assist/dokter/-/blob/main/docs/overview.md
- Dokter: the doctor for your Dockerfiles
clickhouse-operator
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ClickHouse Cloud is now in Public Beta
but this pricing looks excessive.
A single node instance with a fast disk is more than sufficient for most needs: https://hub.docker.com/r/clickhouse/clickhouse-server
If you need a cluster, https://github.com/Altinity/clickhouse-operator makes things easy
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Databases in 2021: A Year in Review
Altinity is doing a good job of this with Clickhouse. They offer some decent open source guides for self hosting[0] and offer a hosted option. The hosted option is as self serve as I'd like (you have to get "approved").
0 - https://github.com/Altinity/clickhouse-operator and
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Show HN: Distributed Tracing Using OpenTelemetry and ClickHouse
Where is the clickhouse data stored, in the Docker container?
For reference, here's what I'm using: https://github.com/Altinity/clickhouse-operator/blob/master/...
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What's New in ClickHouse 21.12
ClickHouse works great on Kubernetes. Check out the ClickHouse Operator for Kubernetes. [0] We just added a UI to it, blog article out shortly.
[0] https://github.com/Altinity/clickhouse-operator
Disclaimer: I work at Altinity.
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What is ClickHouse how it compares to PostgreSQL and TimescaleDB for time series
Don't use helm. The ClickHouse Kubernetes Operator is the way to go. Here's the project: https://github.com/Altinity/clickhouse-operator
This is generally true for most databases these days. Use an operator if it's available. Helm can't handle the dynamic management required to run databases properly.
What are some alternatives?
hadolint - Dockerfile linter, validate inline bash, written in Haskell
jaeger-clickhouse - Jaeger ClickHouse storage plugin implementation
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
uptrace - Open source APM: OpenTelemetry traces, metrics, and logs
orchest - Build data pipelines, the easy way 🛠️
django-simple-history - Store model history and view/revert changes from admin site.
v4
signoz - SigNoz is an open-source observability platform native to OpenTelemetry with logs, traces and metrics in a single application. An open-source alternative to DataDog, NewRelic, etc. 🔥 🖥. 👉 Open source Application Performance Monitoring (APM) & Observability tool
ClickBench - ClickBench: a Benchmark For Analytical Databases
vitess - Vitess is a database clustering system for horizontal scaling of MySQL.
databooks - A CLI tool to reduce the friction between data scientists by reducing git conflicts removing notebook metadata and gracefully resolving git conflicts.
dbt-clickhouse - The Clickhouse plugin for dbt (data build tool)