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DBMS > BigchainDB vs. Google Cloud Datastore vs. Microsoft Azure Synapse Analytics vs. Sadas Engine vs. Sphinx

System Properties Comparison BigchainDB vs. Google Cloud Datastore vs. Microsoft Azure Synapse Analytics vs. Sadas Engine vs. Sphinx

Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSadas Engine  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeDocument storeRelational DBMSRelational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.79
Rank#212  Overall
#36  Document stores
Score4.47
Rank#76  Overall
#12  Document stores
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.bigchaindb.comcloud.google.com/­datastoreazure.microsoft.com/­services/­synapse-analyticswww.sadasengine.comsphinxsearch.com
Technical documentationbigchaindb.readthedocs.io/­en/­latestcloud.google.com/­datastore/­docsdocs.microsoft.com/­azure/­synapse-analyticswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationsphinxsearch.com/­docs
DeveloperGoogleMicrosoftSADAS s.r.l.Sphinx Technologies Inc.
Initial release20162008201620062001
Current release8.03.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoAGPL v3commercialcommercialcommercial infofree trial version availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languagePythonC++C++C++
Server operating systemsLinuxhostedhostedAIX
Linux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyes, details hereyesyesno
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.nononono
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like query language (GQL)yesyesSQL-like query language (SphinxQL)
APIs and other access methodsCLI Client
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
Proprietary protocol
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
Java
PHP
.Net
C
C#
C++
Groovy
Java
PHP
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresusing Google App EngineTransact SQLnono
TriggersCallbacks using the Google Apps Enginenonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding, horizontal partitioninghorizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using Paxosyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesAccess rights for users, groups and roles according to SQL-standardno

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More resources
BigchainDBGoogle Cloud DatastoreMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSadas EngineSphinx
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