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DBMS > Google Cloud Datastore vs. Memcached vs. Sphinx vs. Splice Machine

System Properties Comparison Google Cloud Datastore vs. Memcached vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonMemcached  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformIn-memory key-value store, originally intended for cachingOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument storeKey-value storeSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score19.42
Rank#32  Overall
#4  Key-value stores
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitecloud.google.com/­datastorewww.memcached.orgsphinxsearch.comsplicemachine.com
Technical documentationcloud.google.com/­datastore/­docsgithub.com/­memcached/­memcached/­wikisphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperGoogleDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalSphinx Technologies Inc.Splice Machine
Initial release2008200320012014
Current release1.6.25, March 20243.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoBSD licenseOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, 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 languageCC++Java
Server operating systemshostedFreeBSD
Linux
OS X
Unix
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes, details herenonoyes
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.no
Secondary indexesyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like query language (GQL)noSQL-like query language (SphinxQL)yes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Proprietary protocolProprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresusing Google App Enginenonoyes infoJava
TriggersCallbacks using the Google Apps Enginenonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosnone infoRepcached, a Memcached patch, provides this functionallitynoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud DataflownonoYes, via Full Spark Integration
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
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesnoyes 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)yes infousing SASL (Simple Authentication and Security Layer) protocolnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Google Cloud DatastoreMemcachedSphinxSplice Machine
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