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DBMS > BigchainDB vs. Firebase Realtime Database vs. InfinityDB vs. Microsoft Access vs. Splice Machine

System Properties Comparison BigchainDB vs. Firebase Realtime Database vs. InfinityDB vs. Microsoft Access vs. Splice Machine

Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonInfinityDB  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.A Java embedded Key-Value Store which extends the Java Map interfaceMicrosoft 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.)Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument storeDocument storeKey-value storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.79
Rank#212  Overall
#36  Document stores
Score14.29
Rank#39  Overall
#6  Document stores
Score0.00
Rank#378  Overall
#57  Key-value stores
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.bigchaindb.comfirebase.google.com/­products/­realtime-databaseboilerbay.comwww.microsoft.com/­en-us/­microsoft-365/­accesssplicemachine.com
Technical documentationbigchaindb.readthedocs.io/­en/­latestfirebase.google.com/­docs/­databaseboilerbay.com/­infinitydb/­manualdeveloper.microsoft.com/­en-us/­accesssplicemachine.com/­how-it-works
DeveloperGoogle infoacquired by Google 2014Boiler Bay Inc.MicrosoftSplice Machine
Initial release20162012200219922014
Current release4.01902 (16.0.11328.20222), March 20193.1, March 2021
License infoCommercial or Open SourceOpen Source infoAGPL v3commercialcommercialcommercial infoBundled with Microsoft OfficeOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languagePythonJavaC++Java
Server operating systemsLinuxhostedAll OS with a Java VMWindows infoNot a real database server, but making use of DLLsLinux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyesyes
Typing infopredefined data types such as float or datenoyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesyes
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.nonono
Secondary indexesyesno infomanual creation possible, using inversions based on multi-value capabilityyesyes
SQL infoSupport of SQLnononoyes infobut not compliant to any SQL standardyes
APIs and other access methodsCLI Client
RESTful HTTP API
Android
iOS
JavaScript API
RESTful HTTP API
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
ADO.NET
DAO
ODBC
OLE DB
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
Java
JavaScript
Objective-C
JavaC
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored procedureslimited functionality with using 'rules'noyes infosince Access 2010 using the ACE-engineyes infoJava
TriggersCallbacks are triggered when data changesnoyes infosince Access 2010 using the ACE-engineyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornonenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate Consistency
Foreign keys infoReferential integritynonono infomanual creation possible, using inversions based on multi-value capabilityyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID infoOptimistic locking for transactions; no isolation for bulk loadsACID infobut no files for transaction loggingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
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.noyes
User concepts infoAccess controlyesyes, based on authentication and database rulesnono infoa simple user-level security was built in till version Access 2003Access rights for users, groups and roles according to SQL-standard

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More resources
BigchainDBFirebase Realtime DatabaseInfinityDBMicrosoft AccessSplice Machine
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