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DBMS > Amazon Aurora vs. Amazon DocumentDB vs. Microsoft Azure Synapse Analytics vs. Sphinx vs. WakandaDB

System Properties Comparison Amazon Aurora vs. Amazon DocumentDB vs. Microsoft Azure Synapse Analytics vs. Sphinx vs. WakandaDB

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonAmazon DocumentDB  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSphinx  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonFast, scalable, highly available, and fully managed MongoDB-compatible database serviceElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerOpen 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 DBMSDocument storeRelational DBMSSearch 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
Score1.91
Rank#132  Overall
#24  Document stores
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websiteaws.amazon.com/­rds/­auroraaws.amazon.com/­documentdbazure.microsoft.com/­services/­synapse-analyticssphinxsearch.comwakanda.github.io
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlaws.amazon.com/­documentdb/­resourcesdocs.microsoft.com/­azure/­synapse-analyticssphinxsearch.com/­docswakanda.github.io/­doc
DeveloperAmazonMicrosoftSphinx Technologies Inc.Wakanda SAS
Initial release20152019201620012012
Current release3.5.1, February 20232.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C++, JavaScript
Server operating systemshostedhostedhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.yesnonono
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLyesnoyesSQL-like query language (SphinxQL)no
APIs and other access methodsADO.NET
JDBC
ODBC
proprietary protocol using JSON (MongoDB compatible)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
Go
Java
JavaScript (Node.js)
PHP
Python
C#
Java
PHP
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
JavaScript
Server-side scripts infoStored proceduresyesnoTransact SQLnoyes
Triggersyesnononoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnoneSharding, horizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesno infotypically not used, however similar functionality with DBRef possibleno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-document operationsACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and rolesyesnoyes

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More resources
Amazon AuroraAmazon DocumentDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSphinxWakandaDB
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