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DBMS > Google Cloud Datastore vs. PouchDB vs. QuestDB vs. Sphinx

System Properties Comparison Google Cloud Datastore vs. PouchDB vs. QuestDB vs. Sphinx

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonPouchDB  Xexclude from comparisonQuestDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformJavaScript DBMS with an API inspired by CouchDBA high performance open source SQL database for time series dataOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeDocument storeTime Series DBMSSearch engine
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.51
Rank#67  Overall
#10  Document stores
Score3.35
Rank#96  Overall
#17  Document stores
Score0.31
Rank#260  Overall
#20  Time Series DBMS
Score6.35
Rank#59  Overall
#7  Search engines
Websitecloud.google.com/­datastorepouchdb.comquestdb.iosphinxsearch.com
Technical documentationcloud.google.com/­datastore/­docspouchdb.com/­guidesquestdb.io/­docs/­introductionsphinxsearch.com/­docs
DeveloperGoogleApache Software FoundationQuestDB LimitedSphinx Technologies Inc.
Initial release2008201220142001
Current release7.1.1, June 20193.2.1, January 2020
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScriptJavaC++
Server operating systemshostedserver-less, requires a JavaScript environment (browser, Node.js)Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyes infoschema-free via InfluxDB Line Protocolyes
Typing infopredefined data types such as float or dateyes, details herenoyesno
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 indexesyesyes infovia viewsnoyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query language (GQL)noSQL-like query languageSQL-like query language (SphinxQL)
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP REST infoonly for PouchDB Server
JavaScript API
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
Proprietary protocol
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaScriptC infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresusing Google App EngineView functions in JavaScriptnono
TriggersCallbacks using the Google Apps Engineyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infowith a proxy-based framework, named couchdb-loungehorizontal partitioning (by timestamps)Sharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
Configurable consistency for N replicasnone
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.Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes 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.noyesyes infothrough memory mapped files
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono
More information provided by the system vendor
Google Cloud DatastorePouchDBQuestDBSphinx
Specific characteristicsRelational model with native time series support Column based storage and time partitioned...
» more
Competitive advantagesReal-time data ingestion and istant SQL queries for time series High performance...
» more
Typical application scenariosApplication metrics Financial market data and algo trading DevOps monitoring Real-time...
» more
Licensing and pricing modelsApache 2.0.
» more

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More resources
Google Cloud DatastorePouchDBQuestDBSphinx
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