DBMS > Axibase vs. JanusGraph vs. Microsoft SQL Server vs. Sadas Engine vs. UniData,UniVerse

System Properties Comparison Axibase vs. JanusGraph vs. Microsoft SQL Server vs. Sadas Engine vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

A Graph DBMS optimized for distributed clusters

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

Microsofts flagship relational DBMS

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Website

axibase.com/docs/atsd/finance

janusgraph.org

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

www.sadasengine.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

docs.janusgraph.org

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

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Axibase Corporation

Linux Foundation; originally developed as Titan by Aurelius

Microsoft

SADAS s.r.l.

Rocket Software

Initial release

2013

2017

1989

2006

1985

Current release

15585

0.6.3, February 2023

SQL Server 2022, November 2022

8.0

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

free trial version available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Server operating systems

Linux

Linux
OS X
Unix
Windows

Linux
Windows

AIX
Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

yes

optional

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

SQL-like query language

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

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

JDBC
ODBC
Proprietary protocol

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

Go
Java
PHP
Python
R
Ruby

Clojure
Java
Python

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

yes

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

yes

Triggers

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

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

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

yes, but depending on the SQL-Server Edition

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

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

configurable

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

managed by 'Learn by Usage'

User concepts

Access control

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

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

Access rights according to SQL-standard and operating system based

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