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DBMS > BigchainDB vs. Citus vs. Faircom DB vs. Heroic vs. Spark SQL

System Properties Comparison BigchainDB vs. Citus vs. Faircom DB vs. Heroic vs. Spark SQL

Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonCitus  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonHeroic  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeRelational DBMSKey-value store
Relational DBMS
Time Series DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.79
Rank#212  Overall
#36  Document stores
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.bigchaindb.comwww.citusdata.comwww.faircom.com/­products/­faircom-dbgithub.com/­spotify/­heroicspark.apache.org/­sql
Technical documentationbigchaindb.readthedocs.io/­en/­latestdocs.citusdata.comdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlspotify.github.io/­heroicspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFairCom CorporationSpotifyApache Software Foundation
Initial release20162010197920142014
Current release8.1, December 2018V12, November 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoAGPL v3Open Source infoAGPL, commercial license also availablecommercial infoRestricted, free version availableOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languagePythonCANSI C, C++JavaScala
Server operating systemsLinuxLinuxAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
OS X
Windows
Data schemeschema-freeyesschema free, schema optional, schema required, partial schema,schema-freeyes
Typing infopredefined data types such as float or datenoyesyes, ANSI SQL Types, JSON, typed binary structuresyesyes
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.noyes infospecific XML type available, but no XML query functionalitynonono
Secondary indexesyesyesyes infovia Elasticsearchno
SQL infoSupport of SQLnoyes infostandard, with numerous extensionsyes, ANSI SQL with proprietary extensionsnoSQL-like DML and DDL statements
APIs and other access methodsCLI Client
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
HQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
ODBC
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes info.Net, JavaScript, C/C++nono
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replication infoother methods possible by using 3rd party extensionsyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDtunable from ACID to Eventually Consistentnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByesYes, tunable from durable to delayed durability to in-memoryyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlyesfine grained access rights according to SQL-standardFine grained access rights according to SQL-standard with additional protections for filesno

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More resources
BigchainDBCitusFaircom DB infoformerly c-treeACEHeroicSpark SQL
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