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DBMS > Google Cloud Datastore vs. Kdb vs. Sphinx vs. Yaacomo

System Properties Comparison Google Cloud Datastore vs. Kdb vs. Sphinx vs. Yaacomo

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonKdb  Xexclude from comparisonSphinx  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHigh performance Time Series DBMSOpen source search engine for searching in data from different sources, e.g. relational databasesOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument storeTime Series DBMS
Vector DBMS
Search engineRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score7.71
Rank#49  Overall
#2  Time Series DBMS
#1  Vector DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitecloud.google.com/­datastorekx.comsphinxsearch.comyaacomo.com
Technical documentationcloud.google.com/­datastore/­docscode.kx.comsphinxsearch.com/­docs
DeveloperGoogleKx Systems, a division of First Derivatives plcSphinx Technologies Inc.Q2WEB GmbH
Initial release20082000 infokdb was released 2000, kdb+ in 200320012009
Current release3.6, May 20183.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercial infofree 32-bit versionOpen Source infoGPL version 2, commercial licence availablecommercial
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 languageqC++
Server operating systemshostedLinux
OS X
Solaris
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Android
Linux
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyesnoyes
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.noyesno
Secondary indexesyesyes infotable attribute 'grouped'yes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like query language (q)SQL-like query language (SphinxQL)yes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Proprietary protocolJDBC
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsno
TriggersCallbacks using the Google Apps Engineyes infowith viewsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supportedhorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowno infosimilar paradigm used for internal processingnono
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnoyes
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
Durability infoSupport for making data persistentyesyesyes 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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)rights management via user accountsnofine grained access rights according to SQL-standard
More information provided by the system vendor
Google Cloud DatastoreKdbSphinxYaacomo
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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Google Cloud DatastoreKdbSphinxYaacomo
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