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DBMS > Amazon Aurora vs. Microsoft Azure Synapse Analytics vs. Oracle Berkeley DB vs. Sphinx vs. WakandaDB

System Properties Comparison Amazon Aurora vs. Microsoft Azure Synapse Analytics vs. Oracle Berkeley DB vs. Sphinx vs. WakandaDB

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSphinx  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonElastic, 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 databasesWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMSRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Search engineObject oriented DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websiteaws.amazon.com/­rds/­auroraazure.microsoft.com/­services/­synapse-analyticswww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlsphinxsearch.comwakanda.github.io
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.microsoft.com/­azure/­synapse-analyticsdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlsphinxsearch.com/­docswakanda.github.io/­doc
DeveloperAmazonMicrosoftOracle infooriginally developed by Sleepycat, which was acquired by OracleSphinx Technologies Inc.Wakanda SAS
Initial release20152016199420012012
Current release18.1.40, May 20203.5.1, February 20232.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infocommercial license availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPLv3, extended commercial license available
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++C++, JavaScript
Server operating systemshostedhostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Windows
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.yesnoyes infoonly with the Berkeley DB XML editionno
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLyesyesyes infoSQL interfaced based on SQLite is availableSQL-like query language (SphinxQL)no
APIs and other access methodsADO.NET
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary protocolRESTful HTTP API
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C#
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
JavaScript
Server-side scripts infoStored proceduresyesTransact SQLnonoyes
Triggersyesnoyes infoonly for the SQL APInoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding, horizontal partitioningnoneSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnoACID
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.yesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardyesnonoyes

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More resources
Amazon AuroraMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseOracle Berkeley DBSphinxWakandaDB
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