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Learn MorePros of MarkLogic
Pros of MySQL
Pros of PostgreSQL
Pros of MarkLogic
- RDF Triples5
- JSON3
- Marklogic is absolutely stable and very fast3
- REST API3
- JavaScript3
- Enterprise3
- Semantics2
- Multi-model DB2
- Bitemporal1
- Tiered Storage1
Pros of MySQL
- Sql796
- Free674
- Easy557
- Widely used527
- Open source486
- High availability180
- Cross-platform support160
- Great community104
- Secure78
- Full-text indexing and searching75
- Fast, open, available25
- SSL support15
- Reliable14
- Robust13
- Enterprise Version8
- Easy to set up on all platforms7
- NoSQL access to JSON data type2
- Relational database1
- Easy, light, scalable1
- Sequel Pro (best SQL GUI)1
- Replica Support1
Pros of PostgreSQL
- Relational database754
- High availability508
- Enterprise class database436
- Sql380
- Sql + nosql303
- Great community171
- Easy to setup145
- Heroku130
- Secure by default128
- Postgis112
- Supports Key-Value48
- Great JSON support46
- Cross platform32
- Extensible30
- Replication26
- Triggers24
- Rollback22
- Multiversion concurrency control21
- Open source20
- Heroku Add-on17
- Stable, Simple and Good Performance14
- Powerful13
- Lets be serious, what other SQL DB would you go for?12
- Good documentation9
- Scalable7
- Intelligent optimizer7
- Reliable6
- Transactional DDL6
- Modern6
- Free5
- One stop solution for all things sql no matter the os5
- Relational database with MVCC4
- Faster Development3
- Full-Text Search3
- Developer friendly3
- Excellent source code2
- search2
- Great DB for Transactional system or Application2
- Full-text1
- Free version1
- Open-source1
- Text1
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Cons of MarkLogic
Cons of MySQL
Cons of PostgreSQL
Cons of MarkLogic
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Cons of MySQL
- Owned by a company with their own agenda15
- Can't roll back schema changes2
Cons of PostgreSQL
- Table/index bloatings9
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- 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 tools integrate with MarkLogic?
What tools integrate with MySQL?
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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.