DBMS > MySQL vs. TerarkDB vs. Transwarp Hippo vs. XTDB

System Properties Comparison MySQL vs. TerarkDB vs. Transwarp Hippo vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Widely used open source RDBMS

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Key/Value like access via memcached API

Key-value store

Vector DBMS

Document store

Secondary database models

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Score	0.00
Rank	#385	Overall
	#16	Vector DBMS

Score	0.13
Rank	#330	Overall
	#45	Document stores

Website

www.mysql.com

github.com/bytedance/terarkdb

www.transwarp.cn/en/subproduct/hippo

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

dev.mysql.com/doc

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

www.xtdb.com/docs

Developer

Oracle

since 2010, originally MySQL AB, then Sun

ByteDance, originally Terark

Juxt Ltd.

Initial release

1995

2016

2023

2019

Current release

9.0.0, July 2024

1.0, May 2023

1.19, September 2021

License

Commercial or Open Source

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

restricted open source version available

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

C++

Clojure

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes, extensible-data-notation format

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

limited SQL, making use of Apache Calcite

APIs and other access methods

ADO.NET
JDBC
ODBC
Proprietary native API

C++ API
Java API

RESTful HTTP API

HTTP REST
JDBC

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C++
Java

C++
Java
Python

Clojure
Java

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Users with fine-grained authorization concept

no user groups or roles

Role based access control and fine grained access rights

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