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DBMS > BigchainDB vs. Datomic vs. Kinetica vs. LMDB vs. Spark SQL

System Properties Comparison BigchainDB vs. Datomic vs. Kinetica vs. LMDB vs. Spark SQL

Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonDatomic  Xexclude from comparisonKinetica  Xexclude from comparisonLMDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityFully vectorized database across both GPUs and CPUsA high performant, light-weight, embedded key-value database librarySpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeRelational DBMSRelational DBMSKey-value storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.85
Rank#208  Overall
#35  Document stores
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score2.09
Rank#121  Overall
#20  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.bigchaindb.comwww.datomic.comwww.kinetica.comwww.symas.com/­symas-embedded-database-lmdbspark.apache.org/­sql
Technical documentationbigchaindb.readthedocs.io/­en/­latestdocs.datomic.comdocs.kinetica.comwww.lmdb.tech/­docspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCognitectKineticaSymasApache Software Foundation
Initial release20162012201220112014
Current release1.0.7075, December 20237.1, August 20210.9.32, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoAGPL v3commercial infolimited edition freecommercialOpen SourceOpen 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 languagePythonJava, ClojureC, C++CScala
Server operating systemsLinuxAll OS with a Java VMLinuxLinux
Unix
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesschema-freeyes
Typing infopredefined data types such as float or datenoyesyesyes
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.nonononono
Secondary indexesyesyesnono
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsnoSQL-like DML and DDL statements
APIs and other access methodsCLI Client
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
Clojure
Java
C++
Java
JavaScript (Node.js)
Python
.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsuser defined functionsnono
TriggersBy using transaction functionsyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone infoBut extensive use of caching in the application peersSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyes infoGPU vRAM or System RAMyesno
User concepts infoAccess controlyesnoAccess rights for users and roles on table levelnono

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More resources
BigchainDBDatomicKineticaLMDBSpark SQL
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