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DBMS > Hazelcast vs. HBase vs. IBM Db2 Event Store vs. Solr

System Properties Comparison Hazelcast vs. HBase vs. IBM Db2 Event Store vs. Solr

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Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonHBase  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionA widely adopted in-memory data gridWide-column store based on Apache Hadoop and on concepts of BigTableDistributed Event Store optimized for Internet of Things use casesA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelKey-value storeWide column storeEvent Store
Time Series DBMS
Search engine
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.46
Rank#61  Overall
#7  Key-value stores
Score27.97
Rank#26  Overall
#2  Wide column stores
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websitehazelcast.comhbase.apache.orgwww.ibm.com/­products/­db2-event-storesolr.apache.org
Technical documentationhazelcast.org/­imdg/­docshbase.apache.org/­book.htmlwww.ibm.com/­docs/­en/­db2-event-storesolr.apache.org/­resources.html
DeveloperHazelcastApache Software Foundation infoApache top-level project, originally developed by PowersetIBMApache Software Foundation
Initial release2008200820172006
Current release5.3.6, November 20232.3.4, January 20212.09.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache version 2commercial infofree developer edition availableOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC and C++Java
Server operating systemsAll OS with a Java VMLinux
Unix
Windows infousing Cygwin
Linux infoLinux, macOS, Windows for the developer additionAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeschema-free, schema definition possibleyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesyes infosupports customizable data types and automatic typing
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.yes infothe object must implement a serialization strategynonoyes
Secondary indexesyesnonoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like query languagenoyes infothrough the embedded Spark runtimeSolr Parallel SQL Interface
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesyes infoCoprocessors in JavayesJava plugins
Triggersyes infoEventsyesnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated MapMulti-source replication
Source-replica replication
Active-active shard replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency or Eventual ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitedSingle row ACID (across millions of columns)nooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes
User concepts infoAccess controlRole-based access controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACfine grained access rights according to SQL-standardyes

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More resources
HazelcastHBaseIBM Db2 Event StoreSolr
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