DBMS > GigaSpaces vs. Ignite vs. InfluxDB vs. Microsoft SQL Server vs. ToroDB

System Properties Comparison GigaSpaces vs. Ignite vs. InfluxDB vs. Microsoft SQL Server vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

DBMS for storing time series, events and metrics

Microsofts flagship relational DBMS

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

Document store

Secondary database models

Graph DBMS
Search engine

Spatial DBMS

with GEO package

Document store
Graph DBMS
Spatial DBMS

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

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

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

www.gigaspaces.com

ignite.apache.org

www.influxdata.com/products/influxdb-overview

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

github.com/torodb/server

Technical documentation

docs.gigaspaces.com/latest/landing.html

apacheignite.readme.io/docs

docs.influxdata.com/influxdb

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

Developer

Gigaspaces Technologies

Apache Software Foundation

Microsoft

8Kdata

Initial release

2000

2015

2013

1989

2016

Current release

15.5, September 2020

Apache Ignite 2.6

2.7.6, April 2024

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache 2.0

Open Source

MIT-License; commercial enterprise version available

commercial

restricted free version is available

Open Source

AGPL-V3

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++, .Net

C++, Java, .Net

C++

Java

Server operating systems

Linux
macOS
Solaris
Windows

Linux
OS X
Solaris
Windows

Linux
OS X

through Homebrew

Linux
Windows

All OS with a Java 7 VM

Data scheme

schema-free

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data and Strings

yes

string, integer, double, boolean, date, object_id

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-99 for query and DML statements

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language

yes

APIs and other access methods

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

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

HTTP API
JSON over UDP

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

Supported programming languages

.Net
C++
Java
Python
Scala

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

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

Server-side scripts

Stored procedures

yes

yes (compute grid and cache interceptors can be used instead)

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

Triggers

yes, event driven architecture

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes (replicated cache)

selectable replication factor

in enterprise version only

yes, but depending on the SQL-Server Edition

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

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

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

Depending on used storage engine

yes

User concepts

Access control

Role-based access control

Security Hooks for custom implementations

simple rights management via user accounts

fine grained access rights according to SQL-standard

Access rights for users and roles

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