DBMS > GigaSpaces vs. Microsoft Azure Table Storage vs. XTDB

System Properties Comparison GigaSpaces vs. Microsoft Azure Table Storage vs. XTDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Wide column store

Document store

Secondary database models

Graph DBMS
Search engine

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	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.gigaspaces.com

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

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.gigaspaces.com/latest/landing.html

www.xtdb.com/docs

Developer

Gigaspaces Technologies

Microsoft

Juxt Ltd.

Initial release

2000

2012

2019

Current release

15.5, September 2020

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

commercial

Open Source

MIT 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

Clojure

Server operating systems

Linux
macOS
Solaris
Windows

hosted

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

Secondary indexes

yes

SQL

Support of SQL

SQL-99 for query and DML statements

limited SQL, making use of Apache Calcite

APIs and other access methods

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

RESTful HTTP API

HTTP REST
JDBC

Supported programming languages

.Net
C++
Java
Python
Scala

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

Clojure
Java

Server-side scripts

Stored procedures

yes

Triggers

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

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

yes, each node contains all data

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

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

Access rights based on private key authentication or shared access signatures

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

GigaSpaces to hand out almost $14 million in dividends following Cloudify’s acquisition by Dell
19 July 2023, CTech

GigaSpaces' New Cloudify Player Designed for OpenStack
11 December 2023, Channel Futures

Data Sciences Corporation partners with GigaSpaces Technologies to usher DIH technology to enterprises in SA
10 October 2023, ITWeb

GigaSpaces Announces Version 16.0 with Breakthrough Data Integration Tools to Ease Enterprises' Digital ...
3 November 2021, PR Newswire

GigaSpaces Spins Off Cloudify, Its Open Source Cloud Orchestration Unit
27 July 2017, Data Center Knowledge

provided by Google News

Azure Cosmos DB Data Migration tool imports from Azure Table storage | Azure updates
5 May 2015, azure.microsoft.com

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

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

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

Testing Precompiled Azure Functions Locally with Storage Emulator
8 March 2018, Visual Studio Magazine

provided by Google News

Share this page