tsbs
fast-sqlite3-inserts
tsbs | fast-sqlite3-inserts | |
---|---|---|
76 | 11 | |
1,216 | 363 | |
1.2% | - | |
1.9 | 0.0 | |
about 1 month ago | about 1 year ago | |
Go | Rust | |
MIT License | 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.
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.
fast-sqlite3-inserts
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SQLite performance tuning: concurrent reads, multiple GBs and 100k SELECTs/s
I am experimenting with SQLite, where I try inserting 1B rows in under a minute. The current best is inserting 100M rows at 23s. I cut many corners to get performance, but the tweaks might suit your workload.
I have explained my rationale and approach here - https://avi.im/blag/2021/fast-sqlite-inserts/
the repo link - https://github.com/avinassh/fast-sqlite3-inserts
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I/O is no longer the bottleneck
I am working on a project [0] to generate 1 billion rows in SQLite under a minute and inserted 100M rows inserts in 33 seconds. First, I generate the rows and insert them in an in-memory database, then flush them to the disk at the end. To flush it to disk it takes only 2 seconds, so 99% of the time is being spent generating and adding rows to the in-memory B Tree.
For Python optimisation, have you tried PyPy? I ran my same code (zero changes) using PyPy, and I got 3.5x better speed.
I published my findings here [1].
[0] - https://github.com/avinassh/fast-sqlite3-inserts
[1] - https://avi.im/blag/2021/fast-sqlite-inserts/
- Ask HN: Which personal projects got you hired?
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Is there any language that is as similar as possible to Python in syntax, readability, and features, but is statically typed?
I have a side project where I tried to insert one billion rows in SQLite. I was able to insert 100 million rows using Python under 210 seconds. The same thing with PyPy took 120 seconds. I am wondering what kind of speed boost I would get with Cython
- Ask for benchmark. The owner can’t verify a 18% perf gain, could you?
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Inserting One Billion Rows in SQLite Under A Minute
Measure, measure, measure! There is a PR which made really minor changes, but it got 2x speed boost with CPython version
- Inserting One Billion Rows in SQLite Under a Minute
- Weekly Coders, Hackers & All Tech related thread - 17/07/2021
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How we achieved write speeds of 1.4 million rows per second
[somewhat related] Recently, I was benchmarking SQLite inserts and I managed to insert 3.3M records per second (100M in 33 ish seconds) on my local machine - https://github.com/avinassh/fast-sqlite3-inserts Ofcourse the comparison is not apples to apples, but sharing here if anyone finds it interesting
What are some alternatives?
QuestDB - An open source time-series database for fast ingest and SQL queries
julia - The Julia Programming Language
cql-proxy - A client-side CQL proxy/sidecar.
plum - Multiple dispatch in Python
TimescaleDB - An open-source time-series SQL database optimized for fast ingest and complex queries. Packaged as a PostgreSQL extension.
sqlite_micro_logger_arduino - Fast and Lean Sqlite database logger for Arduino UNO and above
orioledb - OrioleDB – building a modern cloud-native storage engine (... and solving some PostgreSQL wicked problems) 🇺🇦
remixdb - RemixDB: A read- and write-optimized concurrent KV store. Fast point and range queries. Extremely low write-amplification.
dbt-clickhouse - The Clickhouse plugin for dbt (data build tool)
dynamic-dns - An automated dynamic DNS solution for Docker and DigitalOcean
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).