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DBMS > Google Cloud Datastore vs. Hawkular Metrics vs. Sphinx vs. STSdb vs. Valentina Server

System Properties Comparison Google Cloud Datastore vs. Hawkular Metrics vs. Sphinx vs. STSdb vs. Valentina Server

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonSphinx  Xexclude from comparisonSTSdb  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Open source search engine for searching in data from different sources, e.g. relational databasesKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodObject-relational database and reports server
Primary database modelDocument storeTime Series DBMSSearch engineKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.04
Rank#360  Overall
#52  Key-value stores
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitecloud.google.com/­datastorewww.hawkular.orgsphinxsearch.comgithub.com/­STSSoft/­STSdb4www.valentina-db.net
Technical documentationcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidesphinxsearch.com/­docsvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperGoogleCommunity supported by Red HatSphinx Technologies Inc.STS Soft SCParadigma Software
Initial release20082014200120111999
Current release3.5.1, February 20234.0.8, September 20155.7.5
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoGPLv2, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C#
Server operating systemshostedLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
WindowsLinux
OS X
Windows
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyesnoyes infoprimitive types and user defined types (classes)yes
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.nono
Secondary indexesyesnoyes infofull-text index on all search fieldsnoyes
SQL infoSupport of SQLSQL-like query language (GQL)noSQL-like query language (SphinxQL)noyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTProprietary protocol.NET Client APIODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
Java
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresusing Google App Enginenononoyes
TriggersCallbacks using the Google Apps Engineyes infovia Hawkular Alertingnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factor infobased on Cassandranonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownononono
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.Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnonono
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.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nononofine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreHawkular MetricsSphinxSTSdbValentina Server
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