DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > GridGain vs. Heroic vs. RavenDB vs. Yanza

System Properties Comparison GridGain vs. Heroic vs. RavenDB vs. Yanza

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonHeroic  Xexclude from comparisonRavenDB  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseTime Series DBMS for IoT Applications
Primary database modelKey-value store
Relational DBMS
Time Series DBMSDocument storeTime Series DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Websitewww.gridgain.comgithub.com/­spotify/­heroicravendb.netyanza.com
Technical documentationwww.gridgain.com/­docs/­index.htmlspotify.github.io/­heroicravendb.net/­docs
DeveloperGridGain Systems, Inc.SpotifyHibernating RhinosYanza
Initial release2007201420102015
Current releaseGridGain 8.5.15.4, July 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoAGPL version 3, commercial license availablecommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetJavaC#
Server operating systemsLinux
OS X
Solaris
Windows
Linux
macOS
Raspberry Pi
Windows
Windows
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnono
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 indexesyesyes infovia Elasticsearchyesno
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLnoSQL-like query language (RQL)no
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HQL (Heroic Query Language, a JSON-based language)
HTTP API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
HTTP API
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
any language that supports HTTP calls
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)noyesno
Triggersyes (cache interceptors and events)noyesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yesMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)noyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID, Cluster-wide transaction availableno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlSecurity Hooks for custom implementationsAuthorization levels configured per client per databaseno

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
GridGainHeroicRavenDBYanza
Recent citations in the news

GridGain in-memory data and generative AI – Blocks and Files
10 May 2024, Blocks & 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 to Sponsor and Speak at Three Key Industry Events in May 2024
6 May 2024, Martechcube

GridGain to Sponsor, Exhibit at Kafka Summit 2024 in London
12 March 2024, PR Newswire

provided by Google News

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

provided by Google News

RavenDB Launches Version 6.0 Lightning Fast Queries, Data Integrations, Corax Indexing Engine, and Sharding
3 October 2023, PR Newswire

RavenDB Welcomes David Baruc as Chief Revenue Officer: Seasoned Tech Leader to Drive Global Sales and ...
13 June 2023, PR Newswire

Install the NoSQL RavenDB Data System
14 May 2021, The New Stack

RavenDB Adds Graph Queries
15 May 2019, Datanami

How I Created a RavenDB Python Client
23 September 2016, Visual Studio Magazine

provided by Google News



Share this page

Featured Products

Milvus logo

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

SingleStore logo

Build AI apps with Vectors on SQL and JSON with milliseconds response times.
Try it today.

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

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.

Present your product here