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DBMS > Google Cloud Datastore vs. Hazelcast vs. Sphinx vs. Transbase

System Properties Comparison Google Cloud Datastore vs. Hazelcast vs. Sphinx vs. Transbase

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHazelcast  Xexclude from comparisonSphinx  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA widely adopted in-memory data gridOpen source search engine for searching in data from different sources, e.g. relational databasesA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelDocument storeKey-value storeSearch engineRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score5.95
Rank#55  Overall
#5  Search engines
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websitecloud.google.com/­datastorehazelcast.comsphinxsearch.comwww.transaction.de/­en/­products/­transbase.html
Technical documentationcloud.google.com/­datastore/­docshazelcast.org/­imdg/­docssphinxsearch.com/­docswww.transaction.de/­en/­products/­transbase/­features.html
DeveloperGoogleHazelcastSphinx Technologies Inc.Transaction Software GmbH
Initial release2008200820011987
Current release5.3.6, November 20233.5.1, February 2023Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoGPL version 2, commercial licence availablecommercial infofree development license
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 languageJavaC++C and C++
Server operating systemshostedAll OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes, details hereyesnoyes
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.noyes infothe object must implement a serialization strategyno
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like query languageSQL-like query language (SphinxQL)yes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
Proprietary protocolADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresusing Google App Engineyes infoEvent Listeners, Executor Servicesnoyes
TriggersCallbacks using the Google Apps Engineyes infoEventsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infoReplicated MapnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesnono
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 Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsone or two-phase-commit; repeatable reads; read commitednoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlnofine grained access rights according to SQL-standard

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Google Cloud DatastoreHazelcastSphinxTransbase
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