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DBMS > Google Cloud Datastore vs. Hawkular Metrics vs. PouchDB vs. Sphinx vs. STSdb

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

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonPouchDB  Xexclude from comparisonSphinx  Xexclude from comparisonSTSdb  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.JavaScript DBMS with an API inspired by CouchDBOpen 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 method
Primary database modelDocument storeTime Series DBMSDocument storeSearch engineKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Score5.95
Rank#55  Overall
#5  Search engines
Score0.10
Rank#357  Overall
#51  Key-value stores
Websitecloud.google.com/­datastorewww.hawkular.orgpouchdb.comsphinxsearch.comgithub.com/­STSSoft/­STSdb4
Technical documentationcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidepouchdb.com/­guidessphinxsearch.com/­docs
DeveloperGoogleCommunity supported by Red HatApache Software FoundationSphinx Technologies Inc.STS Soft SC
Initial release20082014201220012011
Current release7.1.1, June 20193.5.1, February 20234.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open SourceOpen Source infoGPL version 2, commercial licence availableOpen Source infoGPLv2, commercial license available
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 languageJavaJavaScriptC++C#
Server operating systemshostedLinux
OS X
Windows
server-less, requires a JavaScript environment (browser, Node.js)FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Windows
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes, details hereyesnonoyes infoprimitive types and user defined types (classes)
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.nonono
Secondary indexesyesnoyes infovia viewsyes infofull-text index on all search fieldsno
SQL infoSupport of SQLSQL-like query language (GQL)nonoSQL-like query language (SphinxQL)no
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTHTTP REST infoonly for PouchDB Server
JavaScript API
Proprietary protocol.NET Client API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
JavaScriptC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
Java
Server-side scripts infoStored proceduresusing Google App EnginenoView functions in JavaScriptnono
TriggersCallbacks using the Google Apps Engineyes infovia Hawkular Alertingyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraSharding infowith a proxy-based framework, named couchdb-loungeSharding 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 CassandraMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownoyesnono
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
Eventual Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes 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.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nononono

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More resources
Google Cloud DatastoreHawkular MetricsPouchDBSphinxSTSdb
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