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DBMS > Atos Standard Common Repository vs. GridDB vs. Hazelcast vs. Sphinx

System Properties Comparison Atos Standard Common Repository vs. GridDB vs. Hazelcast vs. Sphinx

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGridDB  Xexclude from comparisonHazelcast  Xexclude from comparisonSphinx  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksScalable in-memory time series database optimized for IoT and Big DataA widely adopted in-memory data gridOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Key-value store
Time Series DBMSKey-value storeSearch engine
Secondary database modelsKey-value store
Relational DBMS
Document store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#123  Overall
#10  Time Series DBMS
Score5.72
Rank#59  Overall
#6  Key-value stores
Score5.97
Rank#56  Overall
#5  Search engines
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorygriddb.nethazelcast.comsphinxsearch.com
Technical documentationdocs.griddb.nethazelcast.org/­imdg/­docssphinxsearch.com/­docs
DeveloperAtos Convergence CreatorsToshiba CorporationHazelcastSphinx Technologies Inc.
Initial release2016201320082001
Current release17035.1, August 20225.3.6, November 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2; commercial licenses availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++JavaC++
Server operating systemsLinuxLinuxAll OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeSchema and schema-less with LDAP viewsyesschema-freeyes
Typing infopredefined data types such as float or dateoptionalyes infonumerical, string, blob, geometry, boolean, timestampyesno
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.yesnoyes infothe object must implement a serialization strategy
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query languageSQL-like query language (SphinxQL)
APIs and other access methodsLDAPJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
Proprietary protocol
Supported programming languagesAll languages with LDAP bindingsC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.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 proceduresnonoyes infoEvent Listeners, Executor Servicesno
Triggersyesyesyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyes infoReplicated Mapnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACID at container levelone 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.yesyesyes
User concepts infoAccess controlLDAP bind authenticationAccess rights for users can be defined per databaseRole-based access controlno

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Atos Standard Common RepositoryGridDBHazelcastSphinx
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