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DBMS > Amazon CloudSearch vs. CrateDB vs. Firebird vs. GeoMesa

System Properties Comparison Amazon CloudSearch vs. CrateDB vs. Firebird vs. GeoMesa

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Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonCrateDB  Xexclude from comparisonFirebird  Xexclude from comparisonGeoMesa  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudDistributed Database based on LuceneFirebird is an open source RDBMS forked from Borland's InterBaseGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.
Primary database modelSearch engineDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSSpatial DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#137  Overall
#12  Search engines
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score20.82
Rank#30  Overall
#18  Relational DBMS
Score0.78
Rank#213  Overall
#4  Spatial DBMS
Websiteaws.amazon.com/­cloudsearchcratedb.comwww.firebirdsql.orgwww.geomesa.org
Technical documentationdocs.aws.amazon.com/­cloudsearchcratedb.com/­docswww.firebirdsql.org/­en/­reference-manualswww.geomesa.org/­documentation/­stable/­user/­index.html
DeveloperAmazonCrateFirebird FoundationCCRi and others
Initial release201220132000 infoAs fork of Borland's InterBase2014
Current release5.0.0, January 20245.0.0, May 2024
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoInitial Developer's Public LicenseOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
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 languageJavaC and C++Scala
Server operating systemshostedAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAIX
FreeBSD
HP-UX
Linux
OS X
server-less infoFirebird Embedded Server
Solaris
Unix
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes
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.nono
Secondary indexesyes infoall search fields are automatically indexedyesyesyes
SQL infoSupport of SQLnoyes, but no triggers and constraints, and PostgreSQL compatibilityyesno
APIs and other access methodsHTTP APIADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
ADO.NET
C/C++ API
JDBC infoJaybird
ODBC
OLE DB
Supported programming languages.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
C
C#
C++
Delphi
Java
JavaScript infoNode.js
Lua
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functions (Javascript)PSQLno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredShardingnonedepending on storage layer
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSConfigurable replication on table/partition-levelSource-replica replicationdepending on storage layer
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
depending on storage layer
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infounique row identifiers can be used for implementing an optimistic concurrency control strategyACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoFeatures a multi-generational MVCC architecture, readers do not block writersyes
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.nodepending on storage layer
User concepts infoAccess controlauthentication via encrypted signaturesrights management via user accountsUsers with fine-grained authorization conceptyes infodepending on the DBMS used for storage
More information provided by the system vendor
Amazon CloudSearchCrateDBFirebirdGeoMesa
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 CloudSearchCrateDBFirebirdGeoMesa
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