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DBMS > BigchainDB vs. BigObject vs. Drizzle vs. Faircom EDGE vs. Splice Machine

System Properties Comparison BigchainDB vs. BigObject vs. Drizzle vs. Faircom EDGE vs. Splice Machine

Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonBigObject  Xexclude from comparisonDrizzle  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonSplice Machine  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsAnalytic DBMS for real-time computations and queriesMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument storeRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.79
Rank#212  Overall
#36  Document stores
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.bigchaindb.combigobject.iowww.faircom.com/­products/­faircom-edgesplicemachine.com
Technical documentationbigchaindb.readthedocs.io/­en/­latestdocs.bigobject.iodocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlsplicemachine.com/­how-it-works
DeveloperBigObject, Inc.Drizzle project, originally started by Brian AkerFairCom CorporationSplice Machine
Initial release20162015200819792014
Current release7.2.4, September 2012V3, October 20203.1, March 2021
License infoCommercial or Open SourceOpen Source infoAGPL v3commercial infofree community edition availableOpen Source infoGNU GPLcommercial infoRestricted, free version availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languagePythonC++ANSI C, C++Java
Server operating systemsLinuxLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
FreeBSD
Linux
OS X
Android
Linux infoARM, x86
Raspbian
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or datenoyesyesyes, ANSI Standard SQL Typesyes
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
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes infowith proprietary extensionsyes infoANSI SQL queriesyes
APIs and other access methodsCLI Client
RESTful HTTP API
fluentd
ODBC
RESTful HTTP API
JDBCADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
C
C++
Java
PHP
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresLuanoyes info.Net, JavaScript, C/C++yes infoJava
Triggersnono infohooks for callbacks inside the server can be used.yesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingFile partitioning infoCustomizable business rules for partitioningShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneMulti-source replication
Source-replica replication
yes infoSynchronous and asynchronous realtime replication based on transaction logsMulti-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 systemnoneImmediate Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infoautomatically between fact table and dimension tablesyesyes infowhen using SQLyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyes infoacross SQL and NoSQLyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlyesnoPluggable authentication mechanisms infoe.g. LDAP, HTTPFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Access rights for users, groups and roles according to SQL-standard

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More resources
BigchainDBBigObjectDrizzleFaircom EDGE infoformerly c-treeEDGESplice Machine
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