DB-EnginesextremeDB - solve IoT connectivity disruptionsEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by Redgate Software

DBMS > GridGain vs. Hyprcubd vs. Microsoft Azure Table Storage

System Properties Comparison GridGain vs. Hyprcubd vs. Microsoft Azure Table Storage

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonHyprcubd  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteServerless Time Series DBMSA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelColumnar
Key-value store
Object oriented DBMS
Relational DBMS
Time Series DBMSWide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.37
Rank#154  Overall
#1  Columnar
#26  Key-value stores
#2  Object oriented DBMS
#70  Relational DBMS
Score3.05
Rank#84  Overall
#6  Wide column stores
Websitewww.gridgain.comhyprcubd.com (offline)azure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationwww.gridgain.com/­docs/­index.html
DeveloperGridGain Systems, Inc.Hyprcubd, Inc.Microsoft
Initial release20072012
Current releaseGridGain 8.5.1
License infoCommercial or Open Sourcecommercial, open sourcecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .Net, Python, REST, SQLGo
Server operating systemsLinux
OS X
Solaris
Windows
z/OS
hostedhosted
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyes infotime, int, uint, float, stringyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesnono
Secondary indexesyesnono
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLSQL-like query languageno
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
gRPC (https)RESTful HTTP API
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)nono
Triggersyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesnoyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlRole-based access control
Security Hooks for custom implementations
token accessAccess 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
GridGainHyprcubdMicrosoft Azure Table Storage
Recent citations in the news

GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2025
10 December 2024, PR Newswire

GridGain Sponsoring Strategic AI and Kafka Conferences This Month
7 December 2024, The Eastern Progress Online

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

The GridGain In-Memory Data Grid
10 July 2024, insideainews.com

GridGain, Apache Ignite founder talks in-memory databases
11 August 2022, TechTarget

provided by Google News

Linking tech to humanity: Hyprcubd integrates collaboration among IoT community
23 December 2020, Startland News

provided by Google News

How to use Azure Table storage in .Net
10 July 2024, InfoWorld

Working with Azure to Use and Manage Data Lakes
23 July 2024, Simplilearn

Inside Azure File Storage
7 October 2015, Microsoft

How to write data to Azure Table Store with an Azure Function
14 April 2017, experts-exchange.com

One way to migrate data from Azure Blob Storage to Amazon S3
16 July 2020, AWS Blog

provided by Google News



Share this page

Featured Products

SingleStore logo

The data platform to build your intelligent applications.
Try it free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here