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DBMS > BigchainDB vs. Google Cloud Bigtable vs. Hazelcast vs. Microsoft Access vs. Trafodion

System Properties Comparison BigchainDB vs. Google Cloud Bigtable vs. Hazelcast vs. Microsoft Access vs. Trafodion

Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A widely adopted in-memory data gridMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Transactional SQL-on-Hadoop DBMS
Primary database modelDocument storeKey-value store
Wide column store
Key-value storeRelational DBMSRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.85
Rank#208  Overall
#35  Document stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score101.16
Rank#11  Overall
#8  Relational DBMS
Websitewww.bigchaindb.comcloud.google.com/­bigtablehazelcast.comwww.microsoft.com/­en-us/­microsoft-365/­accesstrafodion.apache.org
Technical documentationbigchaindb.readthedocs.io/­en/­latestcloud.google.com/­bigtable/­docshazelcast.org/­imdg/­docsdeveloper.microsoft.com/­en-us/­accesstrafodion.apache.org/­documentation.html
DeveloperGoogleHazelcastMicrosoftApache Software Foundation, originally developed by HP
Initial release20162015200819922014
Current release5.3.6, November 20231902 (16.0.11328.20222), March 20192.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoAGPL v3commercialOpen Source infoApache Version 2; commercial licenses availablecommercial infoBundled with Microsoft OfficeOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languagePythonJavaC++C++, Java
Server operating systemsLinuxhostedAll OS with a Java VMWindows infoNot a real database server, but making use of DLLsLinux
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenonoyesyesyes
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.nonoyes infothe object must implement a serialization strategyno
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnonoSQL-like query languageyes infobut not compliant to any SQL standardyes
APIs and other access methodsCLI Client
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
DAO
ODBC
OLE DB
ADO.NET
JDBC
ODBC
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor Servicesyes infosince Access 2010 using the ACE-engineJava Stored Procedures
Triggersnoyes infoEventsyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoReplicated Mapnoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesnoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsone or two-phase-commit; repeatable reads; read commitedACID infobut no files for transaction loggingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByesyesyes infobut no files for transaction loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlno infoa simple user-level security was built in till version Access 2003fine grained access rights according to SQL-standard

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More resources
BigchainDBGoogle Cloud BigtableHazelcastMicrosoft AccessTrafodion
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