DBMS > atoti vs. Datomic vs. Oracle Rdb vs. VoltDB

System Properties Comparison atoti vs. Datomic vs. Oracle Rdb vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Object oriented DBMS

Relational DBMS

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

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

atoti.io

www.datomic.com

www.oracle.com/database/technologies/related/rdb.html

www.voltdb.com

Technical documentation

docs.atoti.io

docs.datomic.com

www.oracle.com/database/technologies/related/rdb-doc.html

docs.voltdb.com

Developer

ActiveViam

Cognitect

Oracle, originally developed by Digital Equipment Corporation (DEC)

VoltDB Inc.

Initial release

2012

1984

2010

Current release

1.0.7075, December 2023

7.4.1.1, 2021

11.3, April 2022

License

Commercial or Open Source

commercial

free versions available

commercial

limited edition free

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java, Clojure

Java, C++

Server operating systems

All OS with a Java VM

HP Open VMS

Linux
OS X

for development

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

yes

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

Multidimensional Expressions (MDX)

yes

only a subset of SQL 99

APIs and other access methods

RESTful HTTP API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Clojure
Java

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Python

yes

Transaction Functions

Java

Triggers

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

none

But extensive use of caching in the application peers

Sharding

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

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

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

yes, on a single node

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

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

yes

Snapshots and command logging

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

User concepts

Access control

Users and roles with access to stored procedures

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