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DBMS > Apache Drill vs. BigchainDB vs. Kinetica vs. Tarantool

System Properties Comparison Apache Drill vs. BigchainDB vs. Kinetica vs. Tarantool

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Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonBigchainDB  Xexclude from comparisonKinetica  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsFully vectorized database across both GPUs and CPUsIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelDocument store
Relational DBMS
Document storeRelational DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#124  Overall
#22  Document stores
#59  Relational DBMS
Score0.85
Rank#208  Overall
#35  Document stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitedrill.apache.orgwww.bigchaindb.comwww.kinetica.comwww.tarantool.io
Technical documentationdrill.apache.org/­docsbigchaindb.readthedocs.io/­en/­latestdocs.kinetica.comwww.tarantool.io/­en/­doc
DeveloperApache Software FoundationKineticaVK
Initial release2012201620122008
Current release1.20.3, January 20237.1, August 20212.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoAGPL v3commercialOpen 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, C++C and C++
Server operating systemsLinux
OS X
Windows
LinuxLinuxBSD
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 dateyesnoyesstring, 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.nononono
Secondary indexesnoyesyes
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantnoSQL-like DML and DDL statementsFull-featured ANSI SQL support
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
CLI Client
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Open binary protocol
Supported programming languagesC++Go
Haskell
Java
JavaScript
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsLua, C and SQL stored procedures
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding, 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 factorSource-replica replicationAsynchronous 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 methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual Consistency depending on configurationCasual 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 datanonoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentDepending on the underlying data sourceyes,with MongoDB ord RethinkDByesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Depending on the underlying data sourceyes infoGPU vRAM or System RAMyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlDepending on the underlying data sourceyesAccess rights for users and roles on table levelAccess 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
Apache DrillBigchainDBKineticaTarantool
DB-Engines blog posts

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

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