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DBMS > Google Cloud Datastore vs. GridGain vs. H2 vs. Weaviate

System Properties Comparison Google Cloud Datastore vs. GridGain vs. H2 vs. Weaviate

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonGridGain  Xexclude from comparisonH2  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformGridGain is an in-memory computing platform, built on Apache IgniteFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.An AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelDocument storeColumnar
Key-value store
Object oriented DBMS
Relational DBMS
Relational DBMSVector DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.13
Rank#71  Overall
#12  Document stores
Score1.48
Rank#150  Overall
#1  Columnar
#26  Key-value stores
#2  Object oriented DBMS
#69  Relational DBMS
Score7.57
Rank#47  Overall
#30  Relational DBMS
Score1.48
Rank#149  Overall
#8  Vector DBMS
Websitecloud.google.com/­datastorewww.gridgain.comwww.h2database.comgithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationcloud.google.com/­datastore/­docswww.gridgain.com/­docs/­index.htmlwww.h2database.com/­html/­main.htmlweaviate.io/­developers/­weaviate
DeveloperGoogleGridGain Systems, Inc.Thomas MuellerWeaviate B.V.
Initial release2008200720052019
Current releaseGridGain 8.5.12.2.220, July 20231.19, May 2023
License infoCommercial or Open Sourcecommercialcommercial, open sourceOpen Source infodual-licence (Mozilla public license, Eclipse public license)Open Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .Net, Python, REST, SQLJavaGo
Server operating systemshostedLinux
OS X
Solaris
Windows
z/OS
All OS with a Java VM
Data schemeschema-freeyesyesyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyes, details hereyesyesyes infostring, int, float, geo point, date, cross reference, fuzzy references
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.noyesnono
Secondary indexesyesyesyesyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDLyesGraphQL is used as query language
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
GraphQL query language
RESTful HTTP/JSON API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
JavaJavaScript / TypeScript
Python
Server-side scripts infoStored proceduresusing Google App Engineyes (compute grid and cache interceptors can be used instead)Java Stored Procedures and User-Defined Functionsno
TriggersCallbacks using the Google Apps Engineyes (cache interceptors and events)yesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes (replicated cache)With clustering: 2 database servers on different computers operate on identical copies of a databaseyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
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.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control
Security Hooks for custom implementations
fine grained access rights according to SQL-standardAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
Google Cloud DatastoreGridGainH2Weaviate
Specific characteristicsWeaviate is an open source vector database that is robust, scalable, cloud-native,...
» more
Competitive advantagesFlexible deployment - Free, open source or fully-managed cloud vector database service...
» more
Typical application scenariosAs a database supporting the development of generative AI and semantic search applications...
» more
Key customersAll companies that have data. ​
» more
Market metricsAs of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more
Licensing and pricing modelsWeaviate is open-source, and free to use. Weaviate is also available as a fully managed...
» more

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More resources
Google Cloud DatastoreGridGainH2Weaviate
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Weaviate, an ANN Database with CRUD support
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