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DBMS > Elasticsearch vs. HugeGraph vs. Immudb vs. Microsoft Azure AI Search vs. Sphinx

System Properties Comparison Elasticsearch vs. HugeGraph vs. Immudb vs. Microsoft Azure AI Search vs. Sphinx

Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonHugeGraph  Xexclude from comparisonImmudb  Xexclude from comparisonMicrosoft Azure AI Search  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 metricA fast-speed and highly-scalable Graph DBMSAn open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.Search-as-a-service for web and mobile app developmentOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelSearch engineGraph DBMSKey-value storeSearch engineSearch engine
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Relational DBMSVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score135.35
Rank#7  Overall
#1  Search engines
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score0.24
Rank#305  Overall
#43  Key-value stores
Score5.59
Rank#63  Overall
#7  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.elastic.co/­elasticsearchgithub.com/­hugegraph
hugegraph.apache.org
github.com/­codenotary/­immudb
immudb.io
azure.microsoft.com/­en-us/­services/­searchsphinxsearch.com
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlhugegraph.apache.org/­docsdocs.immudb.iolearn.microsoft.com/­en-us/­azure/­searchsphinxsearch.com/­docs
DeveloperElasticBaiduCodenotaryMicrosoftSphinx Technologies Inc.
Initial release20102018202020152001
Current release8.6, January 20230.91.2.3, April 2022V13.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoElastic LicenseOpen Source infoApache Version 2.0Open Source infoApache Version 2.0commercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaGoC++
Server operating systemsAll OS with a Java VMLinux
macOS
Unix
BSD
Linux
macOS
Solaris
Windows
z/OS
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesno
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.nononono
Secondary indexesyes infoAll search fields are automatically indexedyes infoalso supports composite index and range indexyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languagenoSQL-like syntaxnoSQL-like query language (SphinxQL)
APIs and other access methodsJava API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
TinkerPop Gremlin
gRPC protocol
PostgreSQL wire protocol
RESTful HTTP APIProprietary protocol
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Groovy
Java
Python
.Net
Go
Java
JavaScript (Node.js)
Python
C#
Java
JavaScript
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesasynchronous Gremlin script jobsnonono
Triggersyes infoby using the 'percolation' featurenononono
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infodepending on used storage backend, e.g. Cassandra and HBaseyes infoImplicit feature of the cloud servicenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectorvia hugegraph-sparknonono
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, allEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoedges in graphnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnono
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 integrationyesnono
User concepts infoAccess controlUsers, roles and permissionsyes infousing Azure authenticationno

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More resources
ElasticsearchHugeGraphImmudbMicrosoft Azure AI SearchSphinx
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