DBMS > SAP HANA vs. Splice Machine vs. TDSQL for MySQL vs. TerminusDB

System Properties Comparison SAP HANA vs. Splice Machine vs. TDSQL for MySQL vs. TerminusDB

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Editorial information provided by DB-Engines

Name

Description

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

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

Primary database model

Relational DBMS

Graph DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Document store
Spatial DBMS

Document store
RDF store

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

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Score	0.85
Rank	#207	Overall
	#97	Relational DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

www.sap.com/products/hana.html

splicemachine.com

www.tencentcloud.com/products/dcdb

terminusdb.com

Technical documentation

help.sap.com/hana

splicemachine.com/how-it-works

www.tencentcloud.com/document/product/1042

terminusdb.github.io/terminusdb/#

Developer

SAP

Splice Machine

Tencent

DataChemist Ltd.

Initial release

2010

2014

2013

2018

Current release

2.0 SPS07 (April 4, 2023), April 2023

3.1, March 2021

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

AGPL 3.0, commercial license available

commercial

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

also available as a cloud based service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Prolog, Rust

Server operating systems

Appliance or cloud-service

Linux
OS X
Solaris
Windows

hosted

Linux

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (WOQL)

APIs and other access methods

JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

JDBC
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

C
C#
C++
Java
PHP
Python
Ruby

JavaScript
Python

Server-side scripts

Stored procedures

SQLScript, R

yes

Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Shared Nothhing Auto-Sharding, Columnar Partitioning

Automatic sharding

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

User concepts

Access control

yes

Access rights for users, groups and roles according to SQL-standard

Users with fine-grained authorization concept

Role-based access control

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