Software Alternatives & Reviews

Materialize VS OctoSQL

Compare Materialize VS OctoSQL and see what are their differences

Materialize logo Materialize

A Streaming Database for Real-Time Applications

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
  • Materialize Landing page
    Landing page //
    2023-08-27
  • OctoSQL Landing page
    Landing page //
    2023-08-26

Materialize videos

Bootstrap Vs. Materialize - Which One Should You Choose?

More videos:

  • Review - Materialize Review | Does it compete with Substance Painter?
  • Review - Why We Don't Need Bootstrap, Tailwind or Materialize

OctoSQL videos

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Category Popularity

0-100% (relative to Materialize and OctoSQL)
Databases
58 58%
42% 42
Database Tools
70 70%
30% 30
Big Data
58 58%
42% 42
Stream Processing
100 100%
0% 0

User comments

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Social recommendations and mentions

Based on our record, Materialize should be more popular than OctoSQL. It has been mentiond 65 times since March 2021. 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.

Materialize mentions (65)

  • Choosing Between a Streaming Database and a Stream Processing Framework in Python
    To fully leverage the data is the new oil concept, companies require a special database designed to manage vast amounts of data instantly. This need has led to different database forms, including NoSQL databases, vector databases, time-series databases, graph databases, in-memory databases, and in-memory data grids. Recent years have seen the rise of cloud-based streaming databases such as RisingWave, Materialize,... - Source: dev.to / 3 months ago
  • We Built a Streaming SQL Engine
    Some recent solutions to this problem include Differential Dataflow and Materialize. It would be neat if postgres adopted something similar for live-updating materialized views. https://github.com/timelydataflow/differential-dataflow. - Source: Hacker News / 7 months ago
  • Ask HN: Who is hiring? (October 2023)
    Materialize | Full-Time | NYC Office or Remote | https://materialize.com Materialize is an Operational Data Warehouse: A cloud data warehouse with streaming internals, built for work that needs action on what’s happening right now. Keep the familiar SQL, keep the proven architecture of cloud warehouses but swap the decades-old batch computation model for an efficient incremental engine to get complex queries that... - Source: Hacker News / 7 months ago
  • Ask HN: Who is hiring? (June 2023)
    Materialize | EM (Compute), Senior PM | New York, New York | https://materialize.com/ You shouldn't have to throw away the database to build with fast-changing data. Keep the familiar SQL, keep the proven architecture of cloud warehouses, but swap the decades-old batch computation model for an efficient incremental engine to get complex queries that are always up-to-date. That is Materialize, the only true SQL... - Source: Hacker News / 11 months ago
  • Ask HN: Who is hiring? (April 2023)
    Materialize | NY, NY | https://materialize.com/ The Cloud Database for Fast-Changing Data. We put a streaming engine in a database, so your team can build real-time data products without the cost, complexity, and development time of stream processing. Cloud team openings: https://grnh.se/0ad6ab6b4us Senior PM openings: https://grnh.se/415c267f4us. - Source: Hacker News / about 1 year ago
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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 / about 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 / about 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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What are some alternatives?

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

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

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

Apache Kafka - Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.

Slicing Pie - Perfect equity splits for Bootstrapped Startups

ClickHouse - ClickHouse is an open-source column-oriented database management system that allows generating analytical data reports in real time.

DSQ - Commandline tool for running SQL queries against JSON, CSV, Excel, Parquet, and more. - GitHub - multiprocessio/dsq: Commandline tool for running SQL queries against JSON, CSV, Excel, Parquet, and ...