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DBMS > Elasticsearch vs. Google Cloud Bigtable vs. Rockset vs. Sphinx

System Properties Comparison Elasticsearch vs. Google Cloud Bigtable vs. Rockset vs. Sphinx

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Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonRockset  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A scalable, reliable search and analytics service in the cloud, built on RocksDBOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelSearch engineKey-value store
Wide column store
Document storeSearch engine
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Relational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score135.35
Rank#7  Overall
#1  Search engines
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.79
Rank#211  Overall
#35  Document stores
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.elastic.co/­elasticsearchcloud.google.com/­bigtablerockset.comsphinxsearch.com
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlcloud.google.com/­bigtable/­docsdocs.rockset.comsphinxsearch.com/­docs
DeveloperElasticGoogleRocksetSphinx Technologies Inc.
Initial release2010201520192001
Current release8.6, January 20233.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoElastic LicensecommercialcommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C++
Server operating systemsAll OS with a Java VMhostedhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnodynamic typingno
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.nonono infoingestion from XML files supported
Secondary indexesyes infoAll search fields are automatically indexednoall fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languagenoRead-only SQL queries, including JOINsSQL-like query language (SphinxQL)
APIs and other access methodsJava API
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP RESTProprietary protocol
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesnonono
Triggersyes infoby using the 'percolation' featurenonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic shardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesInternal replication in Colossus, and regional replication between two clusters in different zonesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectoryesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Memcached and Redis integrationno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and organizations can be defined via Rockset consoleno

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More resources
ElasticsearchGoogle Cloud BigtableRocksetSphinx
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