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DBMS > Google Cloud Bigtable vs. Microsoft Azure Synapse Analytics vs. Microsoft Azure Table Storage vs. Oracle Berkeley DB

System Properties Comparison Google Cloud Bigtable vs. Microsoft Azure Synapse Analytics vs. Microsoft Azure Table Storage vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparison
DescriptionGoogle'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 ServerA Wide Column Store for rapid development using massive semi-structured datasetsWidely used in-process key-value store
Primary database modelKey-value store
Wide column store
Relational DBMSWide column storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Websitecloud.google.com/­bigtableazure.microsoft.com/­services/­synapse-analyticsazure.microsoft.com/­en-us/­services/­storage/­tableswww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationcloud.google.com/­bigtable/­docsdocs.microsoft.com/­azure/­synapse-analyticsdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperGoogleMicrosoftMicrosoftOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release2015201620121994
Current release18.1.40, May 2020
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infocommercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, Java, C++ (depending on the Berkeley DB edition)
Server operating systemshostedhostedhostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or datenoyesyesno
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.nononoyes infoonly with the Berkeley DB XML edition
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoyesnoyes infoSQL interfaced based on SQLite is available
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
Java
PHP
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.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
Server-side scripts infoStored proceduresnoTransact SQLnono
Triggersnononoyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesShardingSharding, horizontal partitioningSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono 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 dataAtomic single-row operationsACIDoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesAccess rights based on private key authentication or shared access signaturesno

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More resources
Google Cloud BigtableMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMicrosoft Azure Table StorageOracle Berkeley DB
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