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DBMS > Amazon CloudSearch vs. CrateDB vs. GridGain vs. Oracle Rdb

System Properties Comparison Amazon CloudSearch vs. CrateDB vs. GridGain vs. Oracle Rdb

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Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonCrateDB  Xexclude from comparisonGridGain  Xexclude from comparisonOracle Rdb  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudDistributed Database based on LuceneGridGain is an in-memory computing platform, built on Apache Ignite
Primary database modelSearch engineDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value store
Relational DBMS
Relational 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
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score1.08
Rank#184  Overall
#85  Relational DBMS
Websiteaws.amazon.com/­cloudsearchcratedb.comwww.gridgain.comwww.oracle.com/­database/­technologies/­related/­rdb.html
Technical documentationdocs.aws.amazon.com/­cloudsearchcratedb.com/­docswww.gridgain.com/­docs/­index.htmlwww.oracle.com/­database/­technologies/­related/­rdb-doc.html
DeveloperAmazonCrateGridGain Systems, Inc.Oracle, originally developed by Digital Equipment Corporation (DEC)
Initial release2012201320071984
Current releaseGridGain 8.5.17.4.1.1, 2021
License infoCommercial or Open SourcecommercialOpen Sourcecommercialcommercial
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 languageJavaJava, C++, .Net
Server operating systemshostedAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
OS X
Solaris
Windows
HP Open VMS
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesFlexible Schema (defined schema, partial schema, schema free)
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.noyesno
Secondary indexesyes infoall search fields are automatically indexedyesyesyes
SQL infoSupport of SQLnoyes, but no triggers and constraints, and PostgreSQL compatibilityANSI-99 for query and DML statements, subset of DDLyes
APIs and other access methodsHTTP APIADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
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++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnouser defined functions (Javascript)yes (compute grid and cache interceptors can be used instead)
Triggersnonoyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSConfigurable replication on table/partition-levelyes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
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 strategyACIDyes, on a single node
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.noyesno
User concepts infoAccess controlauthentication via encrypted signaturesrights management via user accountsSecurity Hooks for custom implementations
More information provided by the system vendor
Amazon CloudSearchCrateDBGridGainOracle Rdb
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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Amazon CloudSearchCrateDBGridGainOracle Rdb
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