DBMS > Datomic vs. HarperDB vs. MySQL vs. Newts vs. XTDB

System Properties Comparison Datomic vs. HarperDB vs. MySQL vs. Newts vs. XTDB

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

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Widely used open source RDBMS

Time Series DBMS based on Cassandra

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

Primary database model

Relational DBMS

Document store

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Document store

Secondary database models

Document store
Spatial DBMS

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.datomic.com

www.harperdb.io

www.mysql.com

opennms.github.io/newts

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

Technical documentation

docs.datomic.com

docs.harperdb.io/docs

dev.mysql.com/doc

github.com/OpenNMS/newts/wiki

www.xtdb.com/docs

Developer

Cognitect

HarperDB

Oracle

since 2010, originally MySQL AB, then Sun

OpenNMS Group

Juxt Ltd.

Initial release

2012

2017

1995

2014

2019

Current release

1.0.7075, December 2023

3.1, August 2021

8.4.0, April 2024

1.19, September 2021

License

Commercial or Open Source

commercial

limited edition free

commercial

free community edition available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache 2.0

Open Source

MIT License

Cloud-based only

Only available as a cloud service

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Implementation language

Java, Clojure

Node.js

C and C++

Java

Clojure

Server operating systems

All OS with a Java VM

Linux
OS X

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

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

Data scheme

yes

dynamic schema

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON data types

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like data manipulation statements

yes

with proprietary extensions

limited SQL, making use of Apache Calcite

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP REST
Java API

HTTP REST
JDBC

Supported programming languages

Clojure
Java

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

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

Java

Clojure
Java

Server-side scripts

Stored procedures

yes

Transaction Functions

Custom Functions

since release 3.1

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

A table resides as a whole on one (or more) nodes in a cluster

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

the nodes on which a table resides can be defined

Multi-source replication
Source-replica replication

selectable replication factor

based on Cassandra

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

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Atomic execution of specific operations

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

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

yes, using LMDB

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

Access rights for users and roles

Users with fine-grained authorization concept

no user groups or roles

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