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DBMS > BigchainDB vs. FatDB vs. Splice Machine vs. Tarantool

System Properties Comparison BigchainDB vs. FatDB vs. Splice Machine vs. Tarantool

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Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonFatDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonTarantool  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsA .NET NoSQL DBMS that can integrate with and extend SQL Server.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelDocument storeDocument store
Key-value store
Relational DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.85
Rank#208  Overall
#35  Document stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitewww.bigchaindb.comsplicemachine.comwww.tarantool.io
Technical documentationbigchaindb.readthedocs.io/­en/­latestsplicemachine.com/­how-it-workswww.tarantool.io/­en/­doc
DeveloperFatCloudSplice MachineVK
Initial release2016201220142008
Current release3.1, March 20212.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoAGPL v3commercialOpen Source infoAGPL 3.0, commercial license availableOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languagePythonC#JavaC and C++
Server operating systemsLinuxWindowsLinux
OS X
Solaris
Windows
BSD
Linux
macOS
Data schemeschema-freeschema-freeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or datenoyesyesstring, double, decimal, uuid, integer, blob, boolean, datetime
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.nono
Secondary indexesyesyesyes
SQL infoSupport of SQLnono infoVia inetgration in SQL ServeryesFull-featured ANSI SQL support
APIs and other access methodsCLI Client
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
Native Spark Datasource
ODBC
Open binary protocol
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
C#C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresyes infovia applicationsyes infoJavaLua, C and SQL stored procedures
Triggersyes infovia applicationsyesyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShared Nothhing Auto-Sharding, Columnar PartitioningSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factorMulti-source replication
Source-replica replication
Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes, cooperative multitasking
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlyesno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles according to SQL-standardAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
BigchainDBFatDBSplice MachineTarantool
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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Recent citations in the news

Using BigchainDB: A Database with Blockchain Characteristics
20 January 2022, Open Source For You

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7 blockchain firms join Bosch led GAIA-X consortium for vehicle identity - Ledger Insights
13 September 2022, Ledger Insights

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