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DBMS > Amazon CloudSearch vs. Microsoft Azure Synapse Analytics vs. Oracle Berkeley DB vs. Sphinx vs. Teradata

System Properties Comparison Amazon CloudSearch vs. Microsoft Azure Synapse Analytics vs. Oracle Berkeley DB vs. Sphinx vs. Teradata

Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSphinx  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerWidely used in-process key-value storeOpen source search engine for searching in data from different sources, e.g. relational databasesA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelSearch engineRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Search engineRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.81
Rank#137  Overall
#12  Search engines
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score44.87
Rank#22  Overall
#15  Relational DBMS
Websiteaws.amazon.com/­cloudsearchazure.microsoft.com/­services/­synapse-analyticswww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlsphinxsearch.comwww.teradata.com
Technical documentationdocs.aws.amazon.com/­cloudsearchdocs.microsoft.com/­azure/­synapse-analyticsdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlsphinxsearch.com/­docsdocs.teradata.com
DeveloperAmazonMicrosoftOracle infooriginally developed by Sleepycat, which was acquired by OracleSphinx Technologies Inc.Teradata
Initial release20122016199420011984
Current release18.1.40, May 20203.5.1, February 2023Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infocommercial license availableOpen Source infoGPL version 2, commercial licence availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C, Java, C++ (depending on the Berkeley DB edition)C++
Server operating systemshostedhostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
hosted
Linux
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnonoyes
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 infoonly with the Berkeley DB XML editionyes
Secondary indexesyes infoall search fields are automatically indexedyesyesyes infofull-text index on all search fieldsyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLnoyesyes infoSQL interfaced based on SQLite is availableSQL-like query language (SphinxQL)yes infoSQL 2016 + extensions
APIs and other access methodsHTTP APIADO.NET
JDBC
ODBC
Proprietary protocol.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesC#
Java
PHP
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnoTransact SQLnonoyes infoUDFs, stored procedures, table functions in parallel
Triggersnonoyes infoonly for the SQL APInoyes
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredSharding, horizontal partitioningnoneSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSyesSource-replica replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlauthentication via encrypted signaturesyesnonofine grained access rights according to SQL-standard

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More resources
Amazon CloudSearchMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseOracle Berkeley DBSphinxTeradata
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