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DBMS > Elasticsearch vs. Ignite vs. Memcached vs. Spark SQL vs. Yanza

System Properties Comparison Elasticsearch vs. Ignite vs. Memcached vs. Spark SQL vs. Yanza

Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonIgnite  Xexclude from comparisonMemcached  Xexclude from comparisonSpark SQL  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded 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 metricApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.In-memory key-value store, originally intended for cachingSpark SQL is a component on top of 'Spark Core' for structured data processingTime Series DBMS for IoT Applications
Primary database modelSearch engineKey-value store
Relational DBMS
Key-value storeRelational DBMSTime Series DBMS
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
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score19.42
Rank#32  Overall
#4  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.elastic.co/­elasticsearchignite.apache.orgwww.memcached.orgspark.apache.org/­sqlyanza.com
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlapacheignite.readme.io/­docsgithub.com/­memcached/­memcached/­wikispark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperElasticApache Software FoundationDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalApache Software FoundationYanza
Initial release20102015200320142015
Current release8.6, January 2023Apache Ignite 2.61.6.25, March 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoElastic LicenseOpen Source infoApache 2.0Open Source infoBSD licenseOpen Source infoApache 2.0commercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++, Java, .NetCScala
Server operating systemsAll OS with a Java VMLinux
OS X
Solaris
Windows
FreeBSD
Linux
OS X
Unix
Windows
Linux
OS X
Windows
Windows
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesnoyesno
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.noyesnono
Secondary indexesyes infoAll search fields are automatically indexedyesnonono
SQL infoSupport of SQLSQL-like query languageANSI-99 for query and DML statements, subset of DDLnoSQL-like DML and DDL statementsno
APIs and other access methodsJava API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Proprietary protocolJDBC
ODBC
HTTP API
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
Java
Python
R
Scala
any language that supports HTTP calls
Server-side scripts infoStored proceduresyesyes (compute grid and cache interceptors can be used instead)nonono
Triggersyes infoby using the 'percolation' featureyes (cache interceptors and events)nonoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes (replicated cache)none infoRepcached, a Memcached patch, provides this functionallitynonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectoryes (compute grid and hadoop accelerator)nono
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 integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesnoyesyes
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 controlSecurity Hooks for custom implementationsyes infousing SASL (Simple Authentication and Security Layer) protocolnono

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More resources
ElasticsearchIgniteMemcachedSpark SQLYanza
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