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

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

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatomic  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonNSDb  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityFauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.A 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 DBMSDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Graph DBMSTime Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score1.52
Rank#153  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score1.94
Rank#129  Overall
#12  Graph DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Websiteimpala.apache.orgwww.datomic.comfauna.comjanusgraph.orgnsdb.io
Technical documentationimpala.apache.org/­impala-docs.htmldocs.datomic.comdocs.fauna.comdocs.janusgraph.orgnsdb.io/­Architecture
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCognitectFauna, Inc.Linux Foundation; originally developed as Titan by Aurelius
Initial release20132012201420172017
Current release4.1.0, June 20221.0.6735, June 20230.6.3, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infolimited edition freecommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, ClojureScalaJavaJava, Scala
Server operating systemsLinuxAll OS with a Java VMhostedLinux
OS X
Unix
Windows
Linux
macOS
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyesyes: 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.nonononono
Secondary indexesyesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsnononoSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIRESTful HTTP APIJava API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
gRPC
HTTP REST
WebSocket
Supported programming languagesAll languages supporting JDBC/ODBCClojure
Java
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
Clojure
Java
Python
Java
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infoTransaction Functionsuser defined functionsyesno
TriggersnoBy using transaction functionsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peershorizontal partitioning infoconsistent hashingyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone infoBut extensive use of caching in the application peersMulti-source replicationyes
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 integritynonoyesyes 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 persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes 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.noyes inforecommended only for testing and developmentno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoIdentity management, authentication, and access controlUser authentification and security via Rexster Graph Server

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More resources
Apache ImpalaDatomicFauna infopreviously named FaunaDBJanusGraph infosuccessor of TitanNSDb
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