DBMS > Apache Druid vs. Datomic vs. RocksDB vs. Splunk vs. VoltDB

System Properties Comparison Apache Druid vs. Datomic vs. RocksDB vs. Splunk vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Analytics Platform for Big Data

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

Relational DBMS
Time Series DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	89.10
Rank	#14	Overall
	#2	Search engines

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

Technical documentation

druid.apache.org/docs/latest/design

docs.datomic.com

github.com/facebook/rocksdb/wiki

docs.splunk.com/Documentation/Splunk

docs.voltdb.com

Developer

Apache Software Foundation and contributors

Cognitect

Facebook, Inc.

Splunk Inc.

VoltDB Inc.

Initial release

2012

2013

2003

2010

Current release

29.0.1, April 2024

1.0.7075, December 2023

9.2.1, May 2024

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache license v2

commercial

limited edition free

Open Source

BSD

commercial

Limited free edition and free developer edition available

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

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Implementation language

Java

Java, Clojure

C++

Java, C++

Server operating systems

Linux
OS X
Unix

All OS with a Java VM

Linux

Linux
OS X
Solaris
Windows

Linux
OS X

for development

Data scheme

yes

schema-less columns are supported

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

Splunk Search Processing Language for search commands

yes

only a subset of SQL 99

APIs and other access methods

JDBC
RESTful HTTP/JSON API

RESTful HTTP API

C++ API
Java API

HTTP REST

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Clojure
Java

C
C++
Go
Java
Perl
Python
Ruby

C#
Java
JavaScript
PHP
Python
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

Java

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

But extensive use of caching in the application peers

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

But extensive use of caching in the application peers

yes

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

yes

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

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

yes

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights for users and roles

Users and roles with access to stored procedures

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