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DBMS > Elasticsearch vs. Hazelcast vs. Kingbase vs. Teradata Aster

System Properties Comparison Elasticsearch vs. Hazelcast vs. Kingbase vs. Teradata Aster

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Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonHazelcast  Xexclude from comparisonKingbase  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
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 widely adopted in-memory data gridAn enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.Platform for big data analytics on multistructured data sources and types
Primary database modelSearch engineKey-value storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Document store infoJSON support with IMDG 3.12Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score135.35
Rank#7  Overall
#1  Search engines
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.45
Rank#262  Overall
#123  Relational DBMS
Websitewww.elastic.co/­elasticsearchhazelcast.comwww.kingbase.com.cn
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlhazelcast.org/­imdg/­docs
DeveloperElasticHazelcastBeiJing KINGBASE Information technologies inc.Teradata
Initial release2010200819992005
Current release8.6, January 20235.3.6, November 2023V8.0, August 2021
License infoCommercial or Open SourceOpen Source infoElastic LicenseOpen Source infoApache Version 2; commercial licenses availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC and Java
Server operating systemsAll OS with a Java VMAll OS with a Java VMLinux
Windows
Linux
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-freeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesyesyes
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.noyes infothe object must implement a serialization strategyyesyes infoin Aster File Store
Secondary indexesyes infoAll search fields are automatically indexedyesyesyes
SQL infoSupport of SQLSQL-like query languageSQL-like query languageStandard with numerous extensionsyes
APIs and other access methodsJava API
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyesyes infoEvent Listeners, Executor Servicesuser defined functionsR packages
Triggersyes infoby using the 'percolation' featureyes infoEventsyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning (by range, list and hash) and vertical partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoReplicated Mapyesyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectoryesnoyes infoSQL Map-Reduce Framework
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 or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoone or two-phase-commit; repeatable reads; read commitedACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
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 controlRole-based access controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
ElasticsearchHazelcastKingbaseTeradata Aster
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