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DBMS > Amazon CloudSearch vs. Apache Impala vs. Drizzle vs. GridDB

System Properties Comparison Amazon CloudSearch vs. Apache Impala vs. Drizzle vs. GridDB

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Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonApache Impala  Xexclude from comparisonDrizzle  Xexclude from comparisonGridDB  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudAnalytic DBMS for HadoopMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Scalable in-memory time series database optimized for IoT and Big Data
Primary database modelSearch engineRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument storeKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#137  Overall
#12  Search engines
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Websiteaws.amazon.com/­cloudsearchimpala.apache.orggriddb.net
Technical documentationdocs.aws.amazon.com/­cloudsearchimpala.apache.org/­impala-docs.htmldocs.griddb.net
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaDrizzle project, originally started by Brian AkerToshiba Corporation
Initial release2012201320082013
Current release4.1.0, June 20227.2.4, September 20125.1, August 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoGNU GPLOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available
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.
Implementation languageC++C++C++
Server operating systemshostedLinuxFreeBSD
Linux
OS X
Linux
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes infonumerical, string, blob, geometry, boolean, timestamp
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 SQLnoSQL-like DML and DDL statementsyes infowith proprietary extensionsSQL92, SQL-like TQL (Toshiba Query Language)
APIs and other access methodsHTTP APIJDBC
ODBC
JDBCJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Java
PHP
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reducenono
Triggersnonono infohooks for callbacks inside the server can be used.yes
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSselectable replication factorMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID at container level
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.noyes
User concepts infoAccess controlauthentication via encrypted signaturesAccess rights for users, groups and roles infobased on Apache Sentry and KerberosPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users can be defined per database
More information provided by the system vendor
Amazon CloudSearchApache ImpalaDrizzleGridDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Amazon CloudSearchApache ImpalaDrizzleGridDB
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