DBMS > ReductStore vs. SAP HANA vs. SAP SQL Anywhere vs. TerminusDB

System Properties Comparison ReductStore vs. SAP HANA vs. SAP SQL Anywhere vs. TerminusDB

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Editorial information provided by DB-Engines

Name

Description

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

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

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

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

Primary database model

Time Series DBMS

Relational DBMS

Graph DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Document store
RDF store

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

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Score	3.50
Rank	#81	Overall
	#44	Relational DBMS

Score	0.19
Rank	#311	Overall
	#27	Graph DBMS

Website

github.com/reductstore
www.reduct.store

www.sap.com/products/hana.html

www.sap.com/products/technology-platform/sql-anywhere.html

terminusdb.com

Technical documentation

www.reduct.store/docs

help.sap.com/hana

help.sap.com/docs/SAP_SQL_Anywhere

terminusdb.github.io/terminusdb/#

Developer

ReductStore LLC

SAP

formerly Sybase

DataChemist Ltd.

Initial release

2023

2010

1992

2018

Current release

1.9, March 2024

2.0 SPS07 (April 4, 2023), April 2023

17, July 2015

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Business Source License 1.1

commercial

Open Source

GPL V3

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

C++, Rust

Prolog, Rust

Server operating systems

Docker
Linux
macOS
Windows

Appliance or cloud-service

AIX
HP-UX
Linux
OS X
Solaris
Windows

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (WOQL)

APIs and other access methods

HTTP API

JDBC
ODBC

ADO.NET
HTTP API
JDBC
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C++
JavaScript (Node.js)
Python
Rust

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

JavaScript
Python

Server-side scripts

Stored procedures

SQLScript, R

yes, in C/C++, Java, .Net or Perl

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

none

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Database mirroring

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

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

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

fine grained access rights according to SQL-standard

Role-based access control

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