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DBMS > Atos Standard Common Repository vs. CrateDB vs. Hazelcast vs. Warp 10

System Properties Comparison Atos Standard Common Repository vs. CrateDB vs. Hazelcast vs. Warp 10

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonCrateDB  Xexclude from comparisonHazelcast  Xexclude from comparisonWarp 10  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 networksDistributed Database based on LuceneA widely adopted in-memory data gridTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelDocument store
Key-value store
Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value storeTime Series DBMS
Secondary database modelsRelational DBMSDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.14
Rank#344  Overall
#32  Time Series DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorycratedb.comhazelcast.comwww.warp10.io
Technical documentationcratedb.com/­docshazelcast.org/­imdg/­docswww.warp10.io/­content/­02_Getting_started
DeveloperAtos Convergence CreatorsCrateHazelcastSenX
Initial release2016201320082015
Current release17035.3.6, November 2023
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache License 2.0
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.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaJavaJavaJava
Server operating systemsLinuxAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAll OS with a Java VMLinux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or dateoptionalyesyesyes
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 strategyno
Secondary indexesyesyesyesno
SQL infoSupport of SQLnoyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-like query languageno
APIs and other access methodsLDAPADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
HTTP API
Jupyter
WebSocket
Supported programming languagesAll languages with LDAP bindings.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresnouser defined functions (Javascript)yes infoEvent Listeners, Executor Servicesyes infoWarpScript
Triggersyesnoyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyesConfigurable replication on table/partition-levelyes infoReplicated Mapselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Read-after-write consistency on record level
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsno infounique row identifiers can be used for implementing an optimistic concurrency control strategyone or two-phase-commit; repeatable reads; read commitedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes
User concepts infoAccess controlLDAP bind authenticationrights management via user accountsRole-based access controlMandatory use of cryptographic tokens, containing fine-grained authorizations
More information provided by the system vendor
Atos Standard Common RepositoryCrateDBHazelcastWarp 10
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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Atos Standard Common RepositoryCrateDBHazelcastWarp 10
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