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DBMS > Amazon CloudSearch vs. Apache IoTDB vs. Microsoft Access vs. Solr vs. Teradata Aster

System Properties Comparison Amazon CloudSearch vs. Apache IoTDB vs. Microsoft Access vs. Solr vs. Teradata Aster

Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonApache IoTDB  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSolr  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 hosted search engine service by Amazon with the data stored in Amazons cloudAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkMicrosoft 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 LucenePlatform for big data analytics on multistructured data sources and types
Primary database modelSearch engineTime Series DBMSRelational DBMSSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.08
Rank#133  Overall
#12  Search engines
Score1.19
Rank#183  Overall
#15  Time Series DBMS
Score107.93
Rank#11  Overall
#8  Relational DBMS
Score43.91
Rank#24  Overall
#3  Search engines
Websiteaws.amazon.com/­cloudsearchiotdb.apache.orgwww.microsoft.com/­en-us/­microsoft-365/­accesssolr.apache.org
Technical documentationdocs.aws.amazon.com/­cloudsearchiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldeveloper.microsoft.com/­en-us/­accesssolr.apache.org/­resources.html
DeveloperAmazonApache Software FoundationMicrosoftApache Software FoundationTeradata
Initial release20122018199220062005
Current release1.1.0, April 20231902 (16.0.11328.20222), March 20199.5.0, February 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercial infoBundled with Microsoft OfficeOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Java
Server operating systemshostedAll OS with a Java VM (>= 1.8)Windows 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)Linux
Data schemeyesyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsFlexible 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 infosupports customizable data types and automatic typingyes
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.noyesyes infoin Aster File Store
Secondary indexesyes infoall search fields are automatically indexedyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLnoSQL-like query languageyes infobut not compliant to any SQL standardSolr Parallel SQL Interfaceyes
APIs and other access methodsHTTP APIJDBC
Native API
ADO.NET
DAO
ODBC
OLE DB
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Go
Java
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
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoyesyes infosince Access 2010 using the ACE-engineJava pluginsR packages
Triggersnoyesyes infosince Access 2010 using the ACE-engineyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredhorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnoneyesyes 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 methodsnoIntegration with Hadoop and Sparknospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infobut no files for transaction loggingoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlauthentication via encrypted signaturesyesno infoa simple user-level security was built in till version Access 2003yesfine grained access rights according to SQL-standard

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More resources
Amazon CloudSearchApache IoTDBMicrosoft AccessSolrTeradata Aster
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