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DBMS > Google Cloud Datastore vs. OpenTSDB vs. PouchDB vs. SiriDB vs. Sphinx

System Properties Comparison Google Cloud Datastore vs. OpenTSDB vs. PouchDB vs. SiriDB vs. Sphinx

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonOpenTSDB  Xexclude from comparisonPouchDB  Xexclude from comparisonSiriDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformScalable Time Series DBMS based on HBaseJavaScript DBMS with an API inspired by CouchDBOpen Source Time Series DBMSOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeTime Series DBMSDocument storeTime Series DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score1.68
Rank#142  Overall
#12  Time Series DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Score0.07
Rank#378  Overall
#42  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitecloud.google.com/­datastoreopentsdb.netpouchdb.comsiridb.comsphinxsearch.com
Technical documentationcloud.google.com/­datastore/­docsopentsdb.net/­docs/­build/­html/­index.htmlpouchdb.com/­guidesdocs.siridb.comsphinxsearch.com/­docs
DeveloperGooglecurrently maintained by Yahoo and other contributorsApache Software FoundationCesbitSphinx Technologies Inc.
Initial release20082011201220172001
Current release7.1.1, June 20193.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoLGPLOpen SourceOpen Source infoMIT LicenseOpen Source infoGPL version 2, commercial licence 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 languageJavaJavaScriptCC++
Server operating systemshostedLinux
Windows
server-less, requires a JavaScript environment (browser, Node.js)LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes, details herenumeric data for metrics, strings for tagsnoyes infoNumeric datano
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.nononono
Secondary indexesyesnoyes infovia viewsyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query language (GQL)nononoSQL-like query language (SphinxQL)
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Telnet API
HTTP REST infoonly for PouchDB Server
JavaScript API
HTTP APIProprietary protocol
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Erlang
Go
Java
Python
R
Ruby
JavaScriptC
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresusing Google App EnginenoView functions in JavaScriptnono
TriggersCallbacks using the Google Apps Enginenoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on HBaseSharding infowith a proxy-based framework, named couchdb-loungeShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factor infobased on HBaseMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
yesnone
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.Immediate Consistency infobased on HBaseEventual 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 backendyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nonosimple rights management via user accountsno

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More resources
Google Cloud DatastoreOpenTSDBPouchDBSiriDBSphinx
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