DBMS > GeoSpock vs. JanusGraph vs. Microsoft SQL Server vs. SAP HANA vs. SAP IQ

System Properties Comparison GeoSpock vs. JanusGraph vs. Microsoft SQL Server vs. SAP HANA vs. SAP IQ

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Spatial and temporal data processing engine for extreme data scale

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Microsofts flagship relational DBMS

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

Columnar RDBMS optimized for Big Data analytics

Primary database model

Relational DBMS

Graph DBMS

Relational DBMS

column-oriented

Secondary database models

Time Series DBMS

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Website

geospock.com

janusgraph.org

www.microsoft.com/en-us/sql-server

www.sap.com/products/hana.html

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

Technical documentation

docs.janusgraph.org

learn.microsoft.com/en-US/sql/sql-server

help.sap.com/hana

help.sap.com/docs/SAP_IQ

Developer

GeoSpock

Linux Foundation; originally developed as Titan by Aurelius

Microsoft

SAP

SAP, formerly Sybase

Initial release

2017

1989

2010

1994

Current release

2.0, September 2019

0.6.3, February 2023

SQL Server 2022, November 2022

2.0 SPS07 (April 4, 2023), April 2023

16.1 SPS04, April 2019

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

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Implementation language

Java, Javascript

Java

C++

Server operating systems

hosted

Linux
OS X
Unix
Windows

Linux
Windows

Appliance or cloud-service

AIX
HP-UX
Linux
Solaris
Windows

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

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

APIs and other access methods

JDBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
ODBC

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

Clojure
Java
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

SQLScript, R

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

tables can be distributed across several files (horizontal partitioning); sharding through federation

yes

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, but depending on the SQL-Server Edition

yes

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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 can be defined per table

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

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