MapD vs MySQL vs PostgreSQL

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MapD

25
24
+ 1
4
MySQL

122.2K
103.3K
+ 1
3.7K
PostgreSQL

95.6K
80K
+ 1
3.5K
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Pros of MapD
Pros of MySQL
Pros of PostgreSQL
  • 3
    Super fast, and the approach taken
  • 1
    Hehe
  • 800
    Sql
  • 679
    Free
  • 562
    Easy
  • 528
    Widely used
  • 489
    Open source
  • 180
    High availability
  • 160
    Cross-platform support
  • 104
    Great community
  • 78
    Secure
  • 75
    Full-text indexing and searching
  • 25
    Fast, open, available
  • 16
    SSL support
  • 15
    Reliable
  • 14
    Robust
  • 8
    Enterprise Version
  • 7
    Easy to set up on all platforms
  • 2
    NoSQL access to JSON data type
  • 1
    Relational database
  • 1
    Easy, light, scalable
  • 1
    Sequel Pro (best SQL GUI)
  • 1
    Replica Support
  • 762
    Relational database
  • 510
    High availability
  • 439
    Enterprise class database
  • 383
    Sql
  • 304
    Sql + nosql
  • 173
    Great community
  • 147
    Easy to setup
  • 131
    Heroku
  • 130
    Secure by default
  • 113
    Postgis
  • 50
    Supports Key-Value
  • 48
    Great JSON support
  • 34
    Cross platform
  • 32
    Extensible
  • 28
    Replication
  • 26
    Triggers
  • 23
    Rollback
  • 22
    Multiversion concurrency control
  • 21
    Open source
  • 18
    Heroku Add-on
  • 17
    Stable, Simple and Good Performance
  • 15
    Powerful
  • 13
    Lets be serious, what other SQL DB would you go for?
  • 11
    Good documentation
  • 8
    Intelligent optimizer
  • 8
    Free
  • 8
    Scalable
  • 8
    Reliable
  • 7
    Transactional DDL
  • 7
    Modern
  • 6
    One stop solution for all things sql no matter the os
  • 5
    Relational database with MVCC
  • 5
    Faster Development
  • 4
    Developer friendly
  • 4
    Full-Text Search
  • 3
    Free version
  • 3
    Great DB for Transactional system or Application
  • 3
    Relational datanbase
  • 3
    search
  • 3
    Open-source
  • 3
    Excellent source code
  • 2
    Full-text
  • 2
    Text
  • 0
    Native

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Cons of MapD
Cons of MySQL
Cons of PostgreSQL
    Be the first to leave a con
    • 16
      Owned by a company with their own agenda
    • 3
      Can't roll back schema changes
    • 10
      Table/index bloatings

    Sign up to add or upvote consMake informed product decisions

    - No public GitHub repository available -

    What is MapD?

    Interactively query and visualize massive datasets with the parallel power of GPUs.

    What is MySQL?

    The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

    What is PostgreSQL?

    PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

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    What companies use MapD?
    What companies use MySQL?
    What companies use PostgreSQL?

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    What tools integrate with MapD?
    What tools integrate with MySQL?
    What tools integrate with PostgreSQL?

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    Blog Posts

    Dec 22 2021 at 5:41AM

    Pinterest

    MySQLKafkaDruid+3
    3
    569
    Dec 8 2020 at 5:50PM

    DigitalOcean

    GitHubMySQLPostgreSQL+11
    2
    2354
    MySQLKafkaApache Spark+6
    2
    2003
    Nov 20 2019 at 3:38AM

    OneSignal

    PostgreSQLRedisRuby+8
    9
    4639
    Jul 9 2019 at 7:22PM

    Blue Medora

    DockerPostgreSQLNew Relic+8
    11
    2335
    What are some alternatives to MapD, MySQL, and PostgreSQL?
    Tableau
    Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.
    Apache Spark
    Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
    Clickhouse
    It allows analysis of data that is updated in real time. It offers instant results in most cases: the data is processed faster than it takes to create a query.
    MongoDB
    MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
    Microsoft SQL Server
    Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.
    See all alternatives