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DBMS > BigchainDB vs. Datomic vs. Google Cloud Bigtable vs. Microsoft Azure Synapse Analytics vs. Sadas Engine

System Properties Comparison BigchainDB vs. Datomic vs. Google Cloud Bigtable vs. Microsoft Azure Synapse Analytics vs. Sadas Engine

Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonDatomic  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSadas Engine  Xexclude from comparison
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Elastic, 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 environments
Primary database modelDocument storeRelational DBMSKey-value store
Wide column store
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.79
Rank#212  Overall
#36  Document stores
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Websitewww.bigchaindb.comwww.datomic.comcloud.google.com/­bigtableazure.microsoft.com/­services/­synapse-analyticswww.sadasengine.com
Technical documentationbigchaindb.readthedocs.io/­en/­latestdocs.datomic.comcloud.google.com/­bigtable/­docsdocs.microsoft.com/­azure/­synapse-analyticswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperCognitectGoogleMicrosoftSADAS s.r.l.
Initial release20162012201520162006
Current release1.0.6735, June 20238.0
License infoCommercial or Open SourceOpen Source infoAGPL v3commercial infolimited edition freecommercialcommercialcommercial infofree trial version available
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languagePythonJava, ClojureC++C++
Server operating systemsLinuxAll OS with a Java VMhostedhostedAIX
Linux
Windows
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or datenoyesnoyesyes
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.nonononono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLnononoyesyes
APIs and other access methodsCLI Client
RESTful HTTP API
RESTful HTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
Clojure
Java
C#
C++
Go
Java
JavaScript (Node.js)
Python
C#
Java
PHP
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresyes infoTransaction FunctionsnoTransact SQLno
TriggersBy using transaction functionsnonono
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersShardingSharding, horizontal partitioninghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone infoBut extensive use of caching in the application peersInternal replication in Colossus, and regional replication between two clusters in different zonesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnoyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlyesnoAccess 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-standard

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More resources
BigchainDBDatomicGoogle Cloud BigtableMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSadas Engine
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