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DBMS > Cubrid vs. Google Cloud Bigtable vs. Hazelcast vs. Sphinx

System Properties Comparison Cubrid vs. Google Cloud Bigtable vs. Hazelcast vs. Sphinx

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Editorial information provided by DB-Engines
NameCubrid  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHazelcast  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A widely adopted in-memory data gridOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSKey-value store
Wide column store
Key-value storeSearch engine
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.04
Rank#187  Overall
#87  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score5.95
Rank#55  Overall
#5  Search engines
Websitecubrid.com (korean)
cubrid.org (english)
cloud.google.com/­bigtablehazelcast.comsphinxsearch.com
Technical documentationcubrid.org/­manualscloud.google.com/­bigtable/­docshazelcast.org/­imdg/­docssphinxsearch.com/­docs
DeveloperCUBRID Corporation, CUBRID FoundationGoogleHazelcastSphinx Technologies Inc.
Initial release2008201520082001
Current release11.0, January 20215.3.6, November 20233.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++, JavaJavaC++
Server operating systemsLinux
Windows
hostedAll OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesno
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.nonoyes infothe object must implement a serialization strategy
Secondary indexesyesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLyesnoSQL-like query languageSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
ODBC
OLE DB
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JCache
JPA
Memcached protocol
RESTful HTTP API
Proprietary protocol
Supported programming languagesC
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresJava Stored Proceduresnoyes infoEvent Listeners, Executor Servicesno
Triggersyesnoyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoReplicated Mapnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsone or two-phase-commit; repeatable reads; read commitedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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)Role-based access controlno

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CubridGoogle Cloud BigtableHazelcastSphinx
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