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DBMS > Amazon DocumentDB vs. Amazon Redshift vs. CrateDB vs. Postgres-XL

System Properties Comparison Amazon DocumentDB vs. Amazon Redshift vs. CrateDB vs. Postgres-XL

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonAmazon Redshift  Xexclude from comparisonCrateDB  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceLarge scale data warehouse service for use with business intelligence toolsDistributed Database based on LuceneBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelDocument storeRelational DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMS
Secondary database modelsRelational DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score16.88
Rank#35  Overall
#22  Relational DBMS
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#9  Vector DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Websiteaws.amazon.com/­documentdbaws.amazon.com/­redshiftcratedb.comwww.postgres-xl.org
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.aws.amazon.com/­redshiftcratedb.com/­docswww.postgres-xl.org/­documentation
DeveloperAmazon (based on PostgreSQL)Crate
Initial release2019201220132014 infosince 2012, originally named StormDB
Current release10 R1, October 2018
License infoCommercial or Open SourcecommercialcommercialOpen SourceOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud serviceyesyesnono
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 languageCJavaC
Server operating systemshostedhostedAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
macOS
Data schemeschema-freeyesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nononoyes infoXML type, but no XML query functionality
Secondary indexesyesrestrictedyesyes
SQL infoSupport of SQLnoyes infodoes not fully support an SQL-standardyes, but no triggers and constraints, and PostgreSQL compatibilityyes infodistributed, parallel query execution
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
ODBC
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
All languages supporting JDBC/ODBC.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++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresnouser defined functions infoin Pythonuser defined functions (Javascript)user defined functions
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardinghorizontal partitioning
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)nonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes infoinformational only, not enforced by the systemnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDno infounique row identifiers can be used for implementing an optimistic concurrency control strategyACID infoMVCC
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 rolesfine grained access rights according to SQL-standardrights management via user accountsfine grained access rights according to SQL-standard
More information provided by the system vendor
Amazon DocumentDBAmazon RedshiftCrateDBPostgres-XL
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 DocumentDBAmazon RedshiftCrateDBPostgres-XL
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