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DBMS > Amazon DocumentDB vs. Atos Standard Common Repository vs. CrateDB vs. GeoSpock

System Properties Comparison Amazon DocumentDB vs. Atos Standard Common Repository vs. CrateDB vs. GeoSpock

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonCrateDB  Xexclude from comparisonGeoSpock  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksDistributed Database based on LuceneSpatial and temporal data processing engine for extreme data scale
Primary database modelDocument storeDocument store
Key-value store
Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMS
Secondary database modelsRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Websiteaws.amazon.com/­documentdbatos.net/en/convergence-creators/portfolio/standard-common-repositorycratedb.comgeospock.com
Technical documentationaws.amazon.com/­documentdb/­resourcescratedb.com/­docs
DeveloperAtos Convergence CreatorsCrateGeoSpock
Initial release201920162013
Current release17032.0, September 2019
License infoCommercial or Open SourcecommercialcommercialOpen Sourcecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
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 languageJavaJavaJava, Javascript
Server operating systemshostedLinuxAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthosted
Data schemeschema-freeSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesoptionalyesyes
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.noyesnono
Secondary indexesyesyesyestemporal, categorical
SQL infoSupport of SQLnonoyes, but no triggers and constraints, and PostgreSQL compatibilityANSI SQL for query only (using Presto)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)LDAPADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
All 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
Server-side scripts infoStored proceduresnonouser defined functions (Javascript)no
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infocell divisionShardingAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesConfigurable replication on table/partition-level
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Read-after-write consistency on record level
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsAtomic execution of specific operationsno infounique row identifiers can be used for implementing an optimistic concurrency control strategyno
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.yesnono
User concepts infoAccess controlAccess rights for users and rolesLDAP bind authenticationrights management via user accountsAccess rights for users can be defined per table
More information provided by the system vendor
Amazon DocumentDBAtos Standard Common RepositoryCrateDBGeoSpock
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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More resources
Amazon DocumentDBAtos Standard Common RepositoryCrateDBGeoSpock
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