DBMS > Datomic vs. Splunk vs. SurrealDB vs. Trafodion

System Properties Comparison Datomic vs. Splunk vs. SurrealDB vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Analytics Platform for Big Data

A fully ACID transactional, developer-friendly, multi-model DBMS

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Search engine

Document store
Graph DBMS

Relational DBMS

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Score	1.02
Rank	#190	Overall
	#33	Document stores
	#18	Graph DBMS

Website

Technical documentation

docs.datomic.com

docs.splunk.com/Documentation/Splunk

surrealdb.com/docs

trafodion.apache.org/documentation.html

Developer

Cognitect

Splunk Inc.

SurrealDB Ltd

Apache Software Foundation, originally developed by HP

Initial release

2012

2003

2022

2014

Current release

1.0.7075, December 2023

v1.5.0, May 2024

2.3.0, February 2019

License

Commercial or Open Source

commercial

limited edition free

commercial

Limited free edition and free developer edition available

Open Source

Apache 2.0

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, Clojure

Rust

C++, Java

Server operating systems

All OS with a Java VM

Linux
OS X
Solaris
Windows

Linux
macOS
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

Splunk Search Processing Language for search commands

SQL-like query language

yes

APIs and other access methods

RESTful HTTP API

HTTP REST

GraphQL
RESTful HTTP API
WebSocket

ADO.NET
JDBC
ODBC

Supported programming languages

Clojure
Java

C#
Java
JavaScript
PHP
Python
Ruby

Deno
Go
JavaScript (Node.js)
Rust

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

Java Stored Procedures

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Multi-source replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

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

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

User concepts

Access control

Access rights for users and roles

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

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