DBMS > Axibase vs. GigaSpaces vs. IBM Db2 Event Store vs. Microsoft SQL Server

System Properties Comparison Axibase vs. GigaSpaces vs. IBM Db2 Event Store vs. Microsoft SQL Server

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Editorial information provided by DB-Engines

Name

Description

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

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Distributed Event Store optimized for Internet of Things use cases

Microsofts flagship relational DBMS

Primary database model

Time Series DBMS

Document store
Object oriented DBMS

Values are user defined objects

Event Store
Time Series DBMS

Relational DBMS

Secondary database models

Graph DBMS
Search engine

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	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

axibase.com/docs/atsd/finance

www.gigaspaces.com

www.ibm.com/products/db2-event-store

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

Technical documentation

docs.gigaspaces.com/latest/landing.html

www.ibm.com/docs/en/db2-event-store

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

Developer

Axibase Corporation

Gigaspaces Technologies

IBM

Microsoft

Initial release

2013

2000

2017

1989

Current release

15585

15.5, September 2020

2.0

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

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

Open Source

Apache Version 2; Commercial licenses available

commercial

free developer edition available

commercial

restricted free version is available

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

Java, C++, .Net

C and C++

C++

Server operating systems

Linux

Linux
macOS
Solaris
Windows

Linux

Linux, macOS, Windows for the developer addition

Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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

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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

SQL-99 for query and DML statements

yes

through the embedded Spark runtime

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

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

Supported programming languages

Go
Java
PHP
Python
R
Ruby

.Net
C++
Java
Python
Scala

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

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

Server-side scripts

Stored procedures

yes

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

Triggers

yes

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Active-active shard replication

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency

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

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

Role-based access control

fine grained access rights according to SQL-standard

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