DBMS > AnzoGraph DB vs. Riak TS vs. SAP HANA vs. Trafodion vs. Transbase

System Properties Comparison AnzoGraph DB vs. Riak TS vs. SAP HANA vs. Trafodion vs. Transbase

Editorial information provided by DB-Engines

Name

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

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

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

Transactional SQL-on-Hadoop DBMS

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Graph DBMS
RDF store

Time Series DBMS

Relational 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	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

cambridgesemantics.com/anzograph

www.sap.com/products/hana.html

trafodion.apache.org

www.transaction.de/en/products/transbase.html

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

www.tiot.jp/riak-docs/riak/ts/latest

help.sap.com/hana

trafodion.apache.org/documentation.html

www.transaction.de/en/products/transbase/features.html

Developer

Cambridge Semantics

Open Source, formerly Basho Technologies

SAP

Apache Software Foundation, originally developed by HP

Transaction Software GmbH

Initial release

2018

2015

2010

2014

1987

Current release

2.3, January 2021

3.0.0, September 2022

2.0 SPS07 (April 4, 2023), April 2023

2.3.0, February 2019

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

free trial version available

Open Source

commercial

Open Source

Apache 2.0

commercial

free development license

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

Erlang

C++, Java

C and C++

Server operating systems

Linux

Linux
OS X

Appliance or cloud-service

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

yes, limited

yes

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

HTTP API
Native Erlang Interface

JDBC
ODBC

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C++
Java
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

All languages supporting JDBC/ODBC/ADO.Net

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

Erlang

SQLScript, R

Java Stored Procedures

yes

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

selectable replication factor

yes

yes, via HBase

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

links between datasets can be stored

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users and roles

yes

fine grained access rights according to SQL-standard

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