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DBMS > Apache Impala vs. Citus vs. Datomic vs. JanusGraph vs. NSDb

System Properties Comparison Apache Impala vs. Citus vs. Datomic vs. JanusGraph vs. NSDb

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonCitus  Xexclude from comparisonDatomic  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonNSDb  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes
Primary database modelRelational DBMSRelational DBMSRelational DBMSGraph DBMSTime Series DBMS
Secondary database modelsDocument storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score1.94
Rank#129  Overall
#12  Graph DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Websiteimpala.apache.orgwww.citusdata.comwww.datomic.comjanusgraph.orgnsdb.io
Technical documentationimpala.apache.org/­impala-docs.htmldocs.citusdata.comdocs.datomic.comdocs.janusgraph.orgnsdb.io/­Architecture
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCognitectLinux Foundation; originally developed as Titan by Aurelius
Initial release20132010201220172017
Current release4.1.0, June 20228.1, December 20181.0.6735, June 20230.6.3, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoAGPL, commercial license also availablecommercial infolimited edition freeOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CJava, ClojureJavaJava, Scala
Server operating systemsLinuxLinuxAll OS with a Java VMLinux
OS X
Unix
Windows
Linux
macOS
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes: int, bigint, decimal, string
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 indexesyesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infostandard, with numerous extensionsnonoSQL-like query language
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP APIJava API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
gRPC
HTTP REST
WebSocket
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Clojure
Java
Clojure
Java
Python
Java
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes infoTransaction Functionsyesno
TriggersnoyesBy using transaction functionsyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone infoBut extensive use of caching in the application peersyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replication infoother methods possible by using 3rd party extensionsnone infoBut extensive use of caching in the application peersyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyes infovia Faunus, a graph analytics engineno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynoyesnoyes infoRelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, HazelcastUsing Apache Lucene
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes inforecommended only for testing and development
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardnoUser authentification and security via Rexster Graph Server

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More resources
Apache ImpalaCitusDatomicJanusGraph infosuccessor of TitanNSDb
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