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DBMS > Amazon CloudSearch vs. Apache Pinot vs. Graphite vs. OpenTenBase

System Properties Comparison Amazon CloudSearch vs. Apache Pinot vs. Graphite vs. OpenTenBase

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Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonApache Pinot  Xexclude from comparisonGraphite  Xexclude from comparisonOpenTenBase  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyData logging and graphing tool for time series data infoThe storage layer (fixed size database) is called WhisperAn enterprise-level distributed HTAP open source database based on PostgreSQL
Primary database modelSearch engineRelational DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#137  Overall
#12  Search engines
Score0.40
Rank#270  Overall
#125  Relational DBMS
Score4.57
Rank#73  Overall
#5  Time Series DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Websiteaws.amazon.com/­cloudsearchpinot.apache.orggithub.com/­graphite-project/­graphite-webgithub.com/­OpenTenBase/­OpenTenBase
www.opentenbase.org
Technical documentationdocs.aws.amazon.com/­cloudsearchdocs.pinot.apache.orggraphite.readthedocs.iodocs.opentenbase.org
docs.opentenbase.org/­en
DeveloperAmazonApache Software Foundation and contributorsChris DavisOpenAtom Foundation, previously Tencent
Initial release201220152006
Current release1.0.0, September 20232.5, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoBSD-3
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaPython
Server operating systemshostedAll OS with a Java JDK11 or higherLinux
Unix
Linux
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesNumeric data onlyyes
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.no
Secondary indexesyes infoall search fields are automatically indexednoyes
SQL infoSupport of SQLnoSQL-like query languagenoyes
APIs and other access methodsHTTP APIJDBCHTTP API
Sockets
Supported programming languagesGo
Java
Python
JavaScript (Node.js)
Python
C
Go
Java
PHP
Python
Server-side scripts infoStored proceduresnono
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredhorizontal partitioningnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infolockingyes
Durability infoSupport for making data persistentyesyesyes
User concepts infoAccess controlauthentication via encrypted signaturesnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon CloudSearchApache PinotGraphiteOpenTenBase
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Recent citations in the news

Amazon CloudSearch – Start Searching in One Hour for Less Than $100 / Month | Amazon Web Services
12 April 2012, AWS Blog

Amazon CloudSearch – Even Better Searching for Less Than $100/Month | Amazon Web Services
24 March 2014, AWS Blog

Amazon Takes On Google And Microsoft With CloudSearch
16 April 2012, Forbes

AWS, Microsoft and Google should retire these cloud services
2 June 2020, TechTarget

Searching CloudTrail Logs Easily with Amazon CloudSearch | AWS Startups Blog
21 October 2014, AWS Blog

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The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data
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