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DBMS > BigObject vs. EsgynDB vs. Google Cloud Bigtable vs. Microsoft Azure SQL Database vs. Oracle Berkeley DB

System Properties Comparison BigObject vs. EsgynDB vs. Google Cloud Bigtable vs. Microsoft Azure SQL Database vs. Oracle Berkeley DB

Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Database as a Service offering with high compatibility to Microsoft SQL ServerWidely used in-process key-value store
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSKey-value store
Wide column store
Relational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Websitebigobject.iowww.esgyn.cncloud.google.com/­bigtableazure.microsoft.com/­en-us/­products/­azure-sql/­databasewww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationdocs.bigobject.iocloud.google.com/­bigtable/­docsdocs.microsoft.com/­en-us/­azure/­azure-sqldocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperBigObject, Inc.EsgynGoogleMicrosoftOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release20152015201520101994
Current releaseV1218.1.40, May 2020
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialcommercialcommercialOpen Source infocommercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaC++C, Java, C++ (depending on the Berkeley DB edition)
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
LinuxhostedhostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeyesyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesnoyesno
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.nononoyesyes infoonly with the Berkeley DB XML edition
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnoyesyes infoSQL interfaced based on SQLite is available
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
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 proceduresLuaJava Stored ProceduresnoTransact SQLno
Triggersnononoyesyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesyes, with always 3 replicas availableSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic single-row operationsACIDACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardno

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More resources
BigObjectEsgynDBGoogle Cloud BigtableMicrosoft Azure SQL Database infoformerly SQL AzureOracle Berkeley DB
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