MarkLogic vs MySQL vs PostgreSQL

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MarkLogic

39
57
+ 1
26
MySQL

98.3K
81.2K
+ 1
3.7K
PostgreSQL

76.9K
62.2K
+ 1
3.5K
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Pros of MarkLogic
Pros of MySQL
Pros of PostgreSQL
  • 5
    RDF Triples
  • 3
    JSON
  • 3
    Marklogic is absolutely stable and very fast
  • 3
    REST API
  • 3
    JavaScript
  • 3
    Enterprise
  • 2
    Semantics
  • 2
    Multi-model DB
  • 1
    Bitemporal
  • 1
    Tiered Storage
  • 796
    Sql
  • 674
    Free
  • 557
    Easy
  • 527
    Widely used
  • 486
    Open source
  • 180
    High availability
  • 160
    Cross-platform support
  • 104
    Great community
  • 78
    Secure
  • 75
    Full-text indexing and searching
  • 25
    Fast, open, available
  • 15
    SSL support
  • 14
    Reliable
  • 13
    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
  • 754
    Relational database
  • 508
    High availability
  • 436
    Enterprise class database
  • 380
    Sql
  • 303
    Sql + nosql
  • 171
    Great community
  • 145
    Easy to setup
  • 130
    Heroku
  • 128
    Secure by default
  • 112
    Postgis
  • 48
    Supports Key-Value
  • 46
    Great JSON support
  • 32
    Cross platform
  • 30
    Extensible
  • 26
    Replication
  • 24
    Triggers
  • 22
    Rollback
  • 21
    Multiversion concurrency control
  • 20
    Open source
  • 17
    Heroku Add-on
  • 14
    Stable, Simple and Good Performance
  • 13
    Powerful
  • 12
    Lets be serious, what other SQL DB would you go for?
  • 9
    Good documentation
  • 7
    Scalable
  • 7
    Intelligent optimizer
  • 6
    Reliable
  • 6
    Transactional DDL
  • 6
    Modern
  • 5
    Free
  • 5
    One stop solution for all things sql no matter the os
  • 4
    Relational database with MVCC
  • 3
    Faster Development
  • 3
    Full-Text Search
  • 3
    Developer friendly
  • 2
    Excellent source code
  • 2
    search
  • 2
    Great DB for Transactional system or Application
  • 1
    Full-text
  • 1
    Free version
  • 1
    Open-source
  • 1
    Text

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Cons of MarkLogic
Cons of MySQL
Cons of PostgreSQL
    Be the first to leave a con
    • 15
      Owned by a company with their own agenda
    • 2
      Can't roll back schema changes
    • 9
      Table/index bloatings

    Sign up to add or upvote consMake informed product decisions

    - No public GitHub repository available -

    What is MarkLogic?

    MarkLogic is the only Enterprise NoSQL database, bringing all the features you need into one unified system: a document-centric, schema-agnostic, structure-aware, clustered, transactional, secure, database server with built-in search and a full suite of application services.

    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 MarkLogic?
    What companies use MySQL?
    What companies use PostgreSQL?

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    What tools integrate with MarkLogic?
    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
    508
    Dec 8 2020 at 5:50PM

    DigitalOcean

    GitHubMySQLPostgreSQL+11
    2
    2089
    MySQLKafkaApache Spark+6
    2
    1741
    Nov 20 2019 at 3:38AM

    OneSignal

    PostgreSQLRedisRuby+8
    8
    4165
    Jul 9 2019 at 7:22PM

    Blue Medora

    DockerPostgreSQLNew Relic+8
    11
    1892
    What are some alternatives to MarkLogic, MySQL, and PostgreSQL?
    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.
    Neo4j
    Neo4j stores data in nodes connected by directed, typed relationships with properties on both, also known as a Property Graph. It is a high performance graph store with all the features expected of a mature and robust database, like a friendly query language and ACID transactions.
    Oracle
    Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database.
    Cassandra
    Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
    HBase
    Apache HBase is an open-source, distributed, versioned, column-oriented store modeled after Google' Bigtable: A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, HBase provides Bigtable-like capabilities on top of Apache Hadoop.
    See all alternatives