DBMS > GridGain vs. Microsoft Azure Table Storage vs. Sadas Engine vs. Transbase

System Properties Comparison GridGain vs. Microsoft Azure Table Storage vs. Sadas Engine vs. Transbase

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

GridGain is an in-memory computing platform, built on Apache Ignite

A Wide Column Store for rapid development using massive semi-structured datasets

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

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Key-value store
Relational DBMS

Wide column store

Relational DBMS

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

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

www.gridgain.com

azure.microsoft.com/en-us/services/storage/tables

www.sadasengine.com

www.transaction.de/en/products/transbase.html

Technical documentation

www.gridgain.com/docs/index.html

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

www.transaction.de/en/products/transbase/features.html

Developer

GridGain Systems, Inc.

Microsoft

SADAS s.r.l.

Transaction Software GmbH

Initial release

2007

2012

2006

1987

Current release

GridGain 8.5.1

8.0

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

free trial version available

commercial

free development license

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java, C++, .Net

C++

C and C++

Server operating systems

Linux
OS X
Solaris
Windows

hosted

AIX
Linux
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

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

yes

SQL

Support of SQL

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

yes

APIs and other access methods

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

RESTful HTTP API

JDBC
ODBC
Proprietary protocol

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

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

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

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

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

yes

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

optimistic locking

yes

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

managed by 'Learn by Usage'

User concepts

Access control

Security Hooks for custom implementations

Access rights based on private key authentication or shared access signatures

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

GridGain in-memory data and generative AI – Blocks and Files
10 May 2024, Blocks and Files

GridGain's 2023 Growth Positions Company for Strong 2024
25 January 2024, Datanami

GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024
8 February 2024, PR Newswire

GridGain Unified Real-Time Data Platform Version 8.9 Addresses Today's More Complex Real-Time Data Processing ...
12 October 2023, GlobeNewswire

GridGain Showcases Power of Apache Ignite at Community Over Code Conference
5 October 2023, Datanami

provided by Google News

Working with Azure to Use and Manage Data Lakes
7 March 2024, Simplilearn

How to use Azure Table storage in .Net
14 January 2019, InfoWorld

How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB
9 July 2021, hackernoon.com

Inside Azure File Storage
7 October 2015, azure.microsoft.com

How to write data to Azure Table Store with an Azure Function
14 April 2017, Experts Exchange

provided by Google News

Share this page