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DBMS > Amazon DocumentDB vs. Elasticsearch vs. GridGain vs. HEAVY.AI vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. Elasticsearch vs. GridGain vs. HEAVY.AI vs. Sphinx

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonElasticsearch  Xexclude from comparisonGridGain  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA 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 metricGridGain is an in-memory computing platform, built on Apache IgniteA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeSearch engineKey-value store
Relational DBMS
Relational DBMSSearch engine
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score132.83
Rank#7  Overall
#1  Search engines
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websiteaws.amazon.com/­documentdbwww.elastic.co/­elasticsearchwww.gridgain.comgithub.com/­heavyai/­heavydb
www.heavy.ai
sphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourceswww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlwww.gridgain.com/­docs/­index.htmldocs.heavy.aisphinxsearch.com/­docs
DeveloperElasticGridGain Systems, Inc.HEAVY.AI, Inc.Sphinx Technologies Inc.
Initial release20192010200720162001
Current release8.6, January 2023GridGain 8.5.15.10, January 20223.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoElastic LicensecommercialOpen Source infoApache Version 2; enterprise edition availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, C++, .NetC++ and CUDAC++
Server operating systemshostedAll OS with a Java VMLinux
OS X
Solaris
Windows
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesno
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.nonoyesno
Secondary indexesyesyes infoAll search fields are automatically indexedyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like query languageANSI-99 for query and DML statements, subset of DDLyesSQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Java API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Thrift
Vega
Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBC/Thrift
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyesyes (compute grid and cache interceptors can be used instead)nono
Triggersnoyes infoby using the 'percolation' featureyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding infoRound robinSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesyes (replicated cache)Multi-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)ES-Hadoop Connectoryes (compute grid and hadoop accelerator)nono
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, allImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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 integrationyesyes
User concepts infoAccess controlAccess rights for users and rolesSecurity Hooks for custom implementationsfine grained access rights according to SQL-standardno

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More resources
Amazon DocumentDBElasticsearchGridGainHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Sphinx
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