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DBMS > Amazon CloudSearch vs. Databricks vs. OpenSearch

System Properties Comparison Amazon CloudSearch vs. Databricks vs. OpenSearch

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Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonDatabricks  Xexclude from comparisonOpenSearch  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene
Primary database modelSearch engineDocument store
Relational DBMS
Search engine
Vector DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.64
Rank#135  Overall
#12  Search engines
Score102.66
Rank#12  Overall
#2  Document stores
#8  Relational DBMS
Score17.38
Rank#32  Overall
#4  Search engines
#2  Vector DBMS
Websiteaws.amazon.com/­cloudsearchwww.databricks.comgithub.com/­opensearch-project
opensearch.org
Technical documentationdocs.aws.amazon.com/­cloudsearchdocs.databricks.comopensearch.org/­docs/­latest
DeveloperAmazonDatabricksThe OpenSearch Software Foundation
Initial release201220132021
Current release2.19, February 2025
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
STACKIT OpenSearch offers OpenSearch in a managed version in enterprise grade, 100% GDPR-compliant, for a wide range of applications like analytics, website search, offering scalability and fast data access.
Implementation languageJava
Server operating systemshostedhostedAll OS with a Java VM
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-free infoFlexible type definitions. Once a type is defined, it is persistent
Typing infopredefined data types such as float or dateyesyes
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.yes
Secondary indexesyes infoall search fields are automatically indexedyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnowith Databricks SQLSQL-like query language
APIs and other access methodsHTTP APIJDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languagesPython
R
Scala
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby infoElasticsearch client
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyes
Triggersnoyes infoby using the 'percolation' feature
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlauthentication via encrypted signatures

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More resources
Amazon CloudSearchDatabricksOpenSearch
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