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OctoSQL VS InfluxData

Compare OctoSQL VS InfluxData and see what are their differences

OctoSQL logo OctoSQL

OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL. - cube2222/octosql

InfluxData logo InfluxData

Scalable datastore for metrics, events, and real-time analytics.
  • OctoSQL Landing page
    Landing page //
    2023-08-26
  • InfluxData Landing page
    Landing page //
    2023-07-30

OctoSQL videos

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InfluxData videos

Barbara Nelson [InfluxData] | Best Practices for Data Ingestion into InfluxDB

Category Popularity

0-100% (relative to OctoSQL and InfluxData)
Databases
29 29%
71% 71
Big Data
100 100%
0% 0
Time Series Database
0 0%
100% 100
Database Tools
100 100%
0% 0

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare OctoSQL and InfluxData

OctoSQL Reviews

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InfluxData Reviews

ReductStore vs. MinIO & InfluxDB on LTE Network: Who Really Wins the Speed Race?
Maintaining consistency between multiple databases, like MinIO and InfluxDB, adds a layer of complexity. In our setup, MinIO, used for blob storage, is linked to data points in InfluxDB via its filename. Any inconsistencies or mismatches between the two could potentially result in data loss. Furthermore, we need to query both databases, which is quite inefficient. Lastly,...
Apache Druid vs. Time-Series Databases
We occasionally get questions regarding how Apache Druid differs from time-series databases (TSDB) such as InfluxDB or Prometheus, and when to use each technology. This short post serves to help answer these questions.
Source: imply.io
4 Best Time Series Databases To Watch in 2019
InfluxDB is part of the TICK stack : Telegraf, InfluxDB, Chronograf and Kapacitor. InfluxData provides, out of the box, a visualization tool (that can be compared to Grafana), a data processing engine that binds directly with InfluxDB, and a set of more than 50+ agents that can collect real-time metrics for a lot of different data sources.
Source: medium.com

Social recommendations and mentions

Based on our record, OctoSQL seems to be a lot more popular than InfluxData. While we know about 22 links to OctoSQL, we've tracked only 2 mentions of InfluxData. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

OctoSQL mentions (22)

  • Analyzing multi-gigabyte JSON files locally
    OctoSQL[0] or DuckDB[1] will most likely be much simpler, while going through 10 GB of JSON in a couple seconds at most. Disclaimer: author of OctoSQL [0]: https://github.com/cube2222/octosql. - Source: Hacker News / over 1 year ago
  • DuckDB: Querying JSON files as if they were tables
    This is really cool! With their Postgres scanner[0] you can now easily query multiple datasources using SQL and join between them (i.e. Postgres table with JSON file). Something I strived to build with OctoSQL[1] before. It's amazing to see how quickly DuckDB is adding new features. Not a huge fan of C++, which is right now used for authoring extensions, it'd be really cool if somebody implemented a Rust extension... - Source: Hacker News / over 1 year ago
  • Show HN: ClickHouse-local – a small tool for serverless data analytics
    Congrats on the Show HN! It's great to see more tools in this area (querying data from various sources in-place) and the Lambda use case is a really cool idea! I've recently done a bunch of benchmarking, including ClickHouse Local and the usage was straightforward, with everything working as it's supposed to. Just to comment on the performance area though, one area I think ClickHouse could still possibly improve... - Source: Hacker News / over 1 year ago
  • Command-line data analytics made easy
    SPyQL is really cool and its design is very smart, with it being able to leverage normal Python functions! As far as similar tools go, I recommend taking a look at DataFusion[0], dsq[1], and OctoSQL[2]. DataFusion is a very (very very) fast command-line SQL engine but with limited support for data formats. Dsq is based on SQLite which means it has to load data into SQLite first, but then gives you the whole breath... - Source: Hacker News / over 1 year ago
  • Steampipe – Select * from Cloud;
    To add somewhat of a counterpoint to the other response, I've tried the Steampipe CSV plugin and got 50x slower performance vs OctoSQL[0], which is itself 5x slower than something like DataFusion[1]. The CSV plugin doesn't contact any external API's so it should be a good benchmark of the plugin architecture, though it might just not be optimized yet. That said, I don't imagine this ever being a bottleneck for the... - Source: Hacker News / over 1 year ago
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InfluxData mentions (2)

  • Can i log data into excel/csv using aws?
    I would highly recommend using a proper Time Series Database like QuestDB or InfluxDB to do this instead. You can always export data from wither of those two into Excel if your boss wants it in excel, but it's much easier to do data transformations, create graphs and reports, etc. If you have all the data in a proper database. Source: over 2 years ago
  • How to stream IoT data into Excel
    I would suggest using something better suited to IoT data than ... a spreadsheet. I'd recommend looking at one of the Time Series Databases for this. 1) QuestDB or 2) InfluxDB as these are much better suited to streaming data. Source: over 2 years ago

What are some alternatives?

When comparing OctoSQL and InfluxData, you can also consider the following products

LNAV - The Log File Navigator (lnav) is an advanced log file viewer for the console.

TimescaleDB - TimescaleDB is a time-series SQL database providing fast analytics, scalability, with automated data management on a proven storage engine.

DuckDB - DuckDB is an in-process SQL OLAP database management system

Prometheus - An open-source systems monitoring and alerting toolkit.

Materialize - A Streaming Database for Real-Time Applications

MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.