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DBMS > Elasticsearch vs. LeanXcale vs. Microsoft Azure Table Storage

System Properties Comparison Elasticsearch vs. LeanXcale vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonLeanXcale  Xexclude from comparisonMicrosoft Azure Table Storage  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 highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelSearch engineKey-value store
Relational DBMS
Wide column store
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score135.35
Rank#7  Overall
#1  Search engines
Score0.29
Rank#291  Overall
#41  Key-value stores
#132  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Websitewww.elastic.co/­elasticsearchwww.leanxcale.comazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.html
DeveloperElasticLeanXcaleMicrosoft
Initial release201020152012
Current release8.6, January 2023
License infoCommercial or Open SourceOpen Source infoElastic Licensecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemsAll OS with a Java VMhosted
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesschema-free
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.nono
Secondary indexesyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLSQL-like query languageyes infothrough Apache Derbyno
APIs and other access methodsJava API
RESTful HTTP/JSON API
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
RESTful HTTP API
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C
Java
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesno
Triggersyes infoby using the 'percolation' featureno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectornono
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic locking
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.Memcached and Redis integrationyesno
User concepts infoAccess controlAccess rights based on private key authentication or shared access signatures

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More resources
ElasticsearchLeanXcaleMicrosoft Azure Table Storage
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