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DBMS > H2 vs. Hazelcast vs. Microsoft Access vs. Solr

System Properties Comparison H2 vs. Hazelcast vs. Microsoft Access vs. Solr

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Editorial information provided by DB-Engines
NameH2  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.A widely adopted in-memory data gridMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)A widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSKey-value storeRelational DBMSSearch engine
Secondary database modelsSpatial DBMSDocument store infoJSON support with IMDG 3.12Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.13
Rank#49  Overall
#31  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.h2database.comhazelcast.comwww.microsoft.com/­en-us/­microsoft-365/­accesssolr.apache.org
Technical documentationwww.h2database.com/­html/­main.htmlhazelcast.org/­imdg/­docsdeveloper.microsoft.com/­en-us/­accesssolr.apache.org/­resources.html
DeveloperThomas MuellerHazelcastMicrosoftApache Software Foundation
Initial release2005200819922006
Current release2.2.220, July 20235.3.6, November 20231902 (16.0.11328.20222), March 20199.6.0, April 2024
License infoCommercial or Open SourceOpen Source infodual-licence (Mozilla public license, Eclipse public license)Open Source infoApache Version 2; commercial licenses availablecommercial infoBundled with Microsoft OfficeOpen 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++Java
Server operating systemsAll OS with a Java VMAll OS with a Java VMWindows infoNot a real database server, but making use of DLLsAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes 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.noyes infothe object must implement a serialization strategyyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesSQL-like query languageyes infobut not compliant to any SQL standardSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
DAO
ODBC
OLE DB
Java API
RESTful HTTP/JSON API
Supported programming languagesJava.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresJava Stored Procedures and User-Defined Functionsyes infoEvent Listeners, Executor Servicesyes infosince Access 2010 using the ACE-engineJava plugins
Triggersyesyes infoEventsyes infosince Access 2010 using the ACE-engineyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesWith clustering: 2 database servers on different computers operate on identical copies of a databaseyes infoReplicated Mapnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedACID infobut no files for transaction loggingoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access controlno infoa simple user-level security was built in till version Access 2003yes

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More resources
H2HazelcastMicrosoft AccessSolr
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