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DBMS > Cubrid vs. Google Cloud Datastore vs. RRDtool vs. Sphinx

System Properties Comparison Cubrid vs. Google Cloud Datastore vs. RRDtool vs. Sphinx

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Editorial information provided by DB-Engines
NameCubrid  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRRDtool  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformIndustry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database. infoThe data is stored in a circular buffer, thus the system storage footprint remains constant over time.Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSDocument storeTime Series DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.04
Rank#187  Overall
#87  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score1.90
Rank#132  Overall
#11  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitecubrid.com (korean)
cubrid.org (english)
cloud.google.com/­datastoreoss.oetiker.ch/­rrdtoolsphinxsearch.com
Technical documentationcubrid.org/­manualscloud.google.com/­datastore/­docsoss.oetiker.ch/­rrdtool/­docsphinxsearch.com/­docs
DeveloperCUBRID Corporation, CUBRID FoundationGoogleTobias OetikerSphinx Technologies Inc.
Initial release2008200819992001
Current release11.0, January 20211.8.0, 20223.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoGPL V2 and FLOSSOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++, JavaC infoImplementations in Java (e.g. RRD4J) and C# availableC++
Server operating systemsLinux
Windows
hostedHP-UX
Linux
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details hereNumeric data onlyno
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 infoExporting into and restoring from XML files possible
Secondary indexesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLyesSQL-like query language (GQL)noSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
ODBC
OLE DB
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
in-process shared library
Pipes
Proprietary protocol
Supported programming languagesC
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C infowith librrd library
C# infowith a different implementation of RRDTool
Java infowith a different implementation of RRDTool
JavaScript (Node.js) infowith a different implementation of RRDTool
Lua
Perl
PHP infowith a wrapper library
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresJava Stored Proceduresusing Google App Enginenono
TriggersyesCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using Paxosnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
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.none
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoby using the rrdcached daemonyes
Durability infoSupport for making data persistentyesyesyesyes 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.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono

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More resources
CubridGoogle Cloud DatastoreRRDtoolSphinx
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