DBMS > Datomic vs. Vitess vs. XTDB

System Properties Comparison Datomic vs. Vitess vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Scalable, distributed, cloud-native DBMS, extending MySQL

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

Primary database model

Relational DBMS

Document store

Secondary database models

Document store
Spatial DBMS

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

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	0.86
Rank	#202	Overall
	#95	Relational DBMS

Score	0.13
Rank	#330	Overall
	#45	Document stores

Website

www.datomic.com

vitess.io

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

Technical documentation

docs.datomic.com

vitess.io/docs

www.xtdb.com/docs

Developer

Cognitect

The Linux Foundation, PlanetScale

Juxt Ltd.

Initial release

2012

2013

2019

Current release

1.0.7180, July 2024

15.0.2, December 2022

1.19, September 2021

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache Version 2.0, commercial licenses available

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, Clojure

Clojure

Server operating systems

All OS with a Java VM

Docker
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

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.

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

limited SQL, making use of Apache Calcite

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
MySQL protocol
ODBC

HTTP REST
JDBC

Supported programming languages

Clojure
Java

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

Clojure
Java

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

proprietary syntax

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Multi-source replication
Source-replica replication

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

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

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

recommended only for testing and development

yes

User concepts

Access control

Users with fine-grained authorization concept

no user groups or roles

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