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DBMS > DataFS vs. Google Cloud Datastore vs. Oracle Rdb vs. Sphinx vs. Splice Machine

System Properties Comparison DataFS vs. Google Cloud Datastore vs. Oracle Rdb vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameDataFS  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonOracle Rdb  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformOpen 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 modelObject oriented DBMSDocument storeRelational DBMSSearch engineRelational DBMS
Secondary database modelsGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#354  Overall
#15  Object oriented DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score1.08
Rank#184  Overall
#85  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitenewdatabase.comcloud.google.com/­datastorewww.oracle.com/­database/­technologies/­related/­rdb.htmlsphinxsearch.comsplicemachine.com
Technical documentationdev.mobiland.com/­Overview.xspcloud.google.com/­datastore/­docswww.oracle.com/­database/­technologies/­related/­rdb-doc.htmlsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperMobiland AGGoogleOracle, originally developed by Digital Equipment Corporation (DEC)Sphinx Technologies Inc.Splice Machine
Initial release20182008198420012014
Current release1.1.263, October 20227.4.1.1, 20213.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java
Server operating systemsWindowshostedHP Open VMSFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)schema-freeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyes, 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.nonono
Secondary indexesnoyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoSQL-like query language (GQL)yesSQL-like query language (SphinxQL)yes
APIs and other access methods.NET Client API
Proprietary client DLL
WinRT client
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C#
C++
VB.Net
.Net
Go
Java
JavaScript (Node.js)
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 Enginenoyes infoJava
Triggersno, except callback-events from server when changes happenedCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemShardingSharding 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 PaxosnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud DataflownonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 integrityyesyes infovia ReferenceProperties or Ancestor pathsyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsyes, on a single nodenoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes 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.nononoyes
User concepts infoAccess controlWindows-ProfileAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights for users, groups and roles according to SQL-standard

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More resources
DataFSGoogle Cloud DatastoreOracle RdbSphinxSplice Machine
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