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DBMS > Google Cloud Datastore vs. KeyDB vs. Sphinx vs. STSdb

System Properties Comparison Google Cloud Datastore vs. KeyDB vs. Sphinx vs. STSdb

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonKeyDB  Xexclude from comparisonSphinx  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsOpen 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 storeKey-value 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
Score0.70
Rank#229  Overall
#32  Key-value stores
Score5.95
Rank#55  Overall
#5  Search engines
Score0.10
Rank#357  Overall
#51  Key-value stores
Websitecloud.google.com/­datastoregithub.com/­Snapchat/­KeyDB
keydb.dev
sphinxsearch.comgithub.com/­STSSoft/­STSdb4
Technical documentationcloud.google.com/­datastore/­docsdocs.keydb.devsphinxsearch.com/­docs
DeveloperGoogleEQ Alpha Technology Ltd.Sphinx Technologies Inc.STS Soft SC
Initial release2008201920012011
Current release3.5.1, February 20234.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoBSD-3Open Source infoGPL version 2, commercial licence availableOpen Source infoGPLv2, commercial license available
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 languageC++C++C#
Server operating systemshostedLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes, details herepartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesnoyes 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.nono
Secondary indexesyesyes infoby using the Redis Search moduleyes infofull-text index on all search fieldsno
SQL infoSupport of SQLSQL-like query language (GQL)noSQL-like query language (SphinxQL)no
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Proprietary protocol infoRESP - REdis Serialization ProtocoProprietary protocol.NET Client API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
Java
Server-side scripts infoStored proceduresusing Google App EngineLuanono
TriggersCallbacks using the Google Apps Enginenonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replication
Source-replica replication
nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
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
Strong eventual consistency with CRDTs
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 TransactionsOptimistic locking, atomic execution of commands blocks and scriptsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes 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.noyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple password-based access control and ACLnono

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More resources
Google Cloud DatastoreKeyDBSphinxSTSdb
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