DBMS > Datomic vs. Google Cloud Bigtable vs. OrigoDB vs. RDF4J vs. Splunk

System Properties Comparison Datomic vs. Google Cloud Bigtable vs. OrigoDB vs. RDF4J vs. Splunk

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

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

A fully ACID in-memory object graph database

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Analytics Platform for Big Data

Primary database model

Relational DBMS

Key-value store
Wide column store

Document store
Object oriented DBMS

RDF store

Search engine

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

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	2.97
Rank	#92	Overall
	#15	Key-value stores
	#8	Wide column stores

Score	0.00
Rank	#385	Overall
	#54	Document stores
	#21	Object oriented DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	93.02
Rank	#13	Overall
	#2	Search engines

Website

www.datomic.com

cloud.google.com/bigtable

origodb.com

rdf4j.org

www.splunk.com

Technical documentation

docs.datomic.com

cloud.google.com/bigtable/docs

origodb.com/docs

rdf4j.org/documentation

docs.splunk.com/Documentation/Splunk

Developer

Cognitect

Google

Robert Friberg et al

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Splunk Inc.

Initial release

2012

2015

2009

under the name LiveDB

2004

2003

Current release

1.0.7180, July 2024

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Limited free edition and free developer edition available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java, Clojure

Java

Server operating systems

All OS with a Java VM

hosted

Linux
Windows

Linux
OS X
Unix
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

yes

Secondary indexes

yes

SQL

Support of SQL

Splunk Search Processing Language for search commands

APIs and other access methods

RESTful HTTP API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

.NET Client API
HTTP API
LINQ

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP REST

Supported programming languages

Clojure
Java

C#
C++
Go
Java
JavaScript (Node.js)
Python

.Net

Java
PHP
Python

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

Triggers

By using transaction functions

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

horizontal partitioning

client side managed; servers are not synchronized

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Internal replication in Colossus, and regional replication between two clusters in different zones

Source-replica replication

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency

Foreign keys

Referential integrity

depending on model

Transaction concepts

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

ACID

Atomic single-row operations

ACID

Isolation support depends on the API used

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

yes

Write ahead log

yes

in-memory storage is supported as well

yes

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, groups and roles based on Google Cloud Identity and Access Management (IAM)

Role based authorization

Access rights for users and roles

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More resources

DB-Engines blog posts

Enterprise Search Engines almost double their popularity in the last 12 months
2 July 2014, Paul Andlinger

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Recent citations in the news

Nubank released the licenses of its Datomic database
21 May 2023, Desde Linux

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Zoona Case Study
16 December 2017, AWS Blog

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28 July 2020, FinTech Futures

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