DBMS > Realm vs. RocksDB vs. Spark SQL vs. Splunk vs. TerminusDB

System Properties Comparison Realm vs. RocksDB vs. Spark SQL vs. Splunk vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Analytics Platform for Big Data

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Secondary database models

Document store
RDF store

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

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

Technical documentation

realm.io/docs

github.com/facebook/rocksdb/wiki

spark.apache.org/docs/latest/sql-programming-guide.html

docs.splunk.com/Documentation/Splunk

terminusdb.github.io/terminusdb/#

Developer

Realm, acquired by MongoDB in May 2019

Facebook, Inc.

Apache Software Foundation

Splunk Inc.

DataChemist Ltd.

Initial release

2014

2013

2014

2003

2018

Current release

8.11.4, April 2024

3.5.0 ( 2.13), September 2023

11.0.0, January 2023

License

Commercial or Open Source

Open Source

BSD

Open Source

Apache 2.0

commercial

Limited free edition and free developer edition available

Open Source

GPL V3

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

C++

Scala

Prolog, Rust

Server operating systems

Android
Backend: server-less
iOS
Windows

Linux

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Linux

Data scheme

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-like DML and DDL statements

Splunk Search Processing Language for search commands

SQL-like query language (WOQL)

APIs and other access methods

C++ API
Java API

JDBC
ODBC

HTTP REST

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

.Net
Java

with Android only
Objective-C
React Native
Swift

C
C++
Go
Java
Perl
Python
Ruby

Java
Python
R
Scala

C#
Java
JavaScript
PHP
Python
Ruby

JavaScript
Python

Server-side scripts

Stored procedures

runs within the applications so server-side scripts are unnecessary

yes

Triggers

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

yes, utilizing Spark Core

Sharding

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

Multi-source replication

Journaling Streams

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

yes

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

In-Memory realm

yes

User concepts

Access control

yes

Access rights for users and roles

Role-based access control

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