DBMS > Informix vs. JanusGraph vs. Microsoft SQL Server vs. Quasardb

System Properties Comparison Informix vs. JanusGraph vs. Microsoft SQL Server vs. Quasardb

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Editorial information provided by DB-Engines

Name

Description

A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data

A Graph DBMS optimized for distributed clusters

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

Microsofts flagship relational DBMS

Distributed, high-performance timeseries database

Primary database model

Relational DBMS

Since Version 12.10 support for JSON/BSON datatypes compatible with MongoDB

Graph DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

Document store
Graph DBMS
Spatial DBMS

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

Score	17.12
Rank	#34	Overall
	#21	Relational DBMS

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Website

www.ibm.com/products/informix

janusgraph.org

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

quasar.ai

Technical documentation

informix.hcldoc.com
www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html

docs.janusgraph.org

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

doc.quasar.ai/master

Developer

IBM, HCL Technologies

Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.

Linux Foundation; originally developed as Titan by Aurelius

Microsoft

quasardb

Initial release

1984

2017

1989

2009

Current release

14.10.FC5, November 2020

0.6.3, February 2023

SQL Server 2022, November 2022

3.14.1, January 2024

License

Commercial or Open Source

commercial

free developer edition available

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++ and Java

Java

C++

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
OS X
Unix
Windows

Linux
Windows

BSD
Linux
OS X
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Since Version 12.10 support for JSON/BSON datatypes

yes

integer and binary

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

with tags

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

JDBC
JSON API

MongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

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

HTTP API

Supported programming languages

.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Clojure
Java
Python

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

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

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

Triggers

yes

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

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

yes, but depending on the SQL-Server Edition

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

with 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

by using LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

Users with fine-grained authentication, authorization, and auditing controls

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

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