DBMS > Datomic vs. SAP HANA vs. Splunk vs. SurrealDB

System Properties Comparison Datomic vs. SAP HANA vs. Splunk vs. SurrealDB

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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

In-memory, column based data store. Available as appliance or cloud service

Analytics Platform for Big Data

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

Primary database model

Relational DBMS

Search engine

Document store
Graph DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Score	0.86
Rank	#203	Overall
	#34	Document stores
	#18	Graph DBMS

Website

www.datomic.com

www.sap.com/products/hana.html

www.splunk.com

surrealdb.com

Technical documentation

docs.datomic.com

help.sap.com/hana

docs.splunk.com/Documentation/Splunk

surrealdb.com/docs

Developer

Cognitect

SAP

Splunk Inc.

SurrealDB Ltd

Initial release

2012

2010

2003

2022

Current release

1.0.6735, June 2023

2.0 SPS07 (April 4, 2023), April 2023

v1.5.0, May 2024

License

Commercial or Open Source

commercial

limited edition free

commercial

Limited free edition and free developer edition available

Open Source

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java, Clojure

Rust

Server operating systems

All OS with a Java VM

Appliance or cloud-service

Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

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

yes

Splunk Search Processing Language for search commands

SQL-like query language

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

HTTP REST

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

Clojure
Java

C#
Java
JavaScript
PHP
Python
Ruby

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

yes

Transaction Functions

SQLScript, R

yes

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

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

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

Eventual 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

yes

User concepts

Access control

yes

Access rights for users and roles

yes, based on authentication and database rules

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