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DBMS > Apache Impala vs. Datomic vs. Transwarp StellarDB vs. WakandaDB

System Properties Comparison Apache Impala vs. Datomic vs. Transwarp StellarDB vs. WakandaDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatomic  Xexclude from comparisonTranswarp StellarDB  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA distributed graph DBMS built for enterprise-level graph applicationsWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMSRelational DBMSGraph DBMSObject oriented DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score0.07
Rank#371  Overall
#39  Graph DBMS
Score0.10
Rank#356  Overall
#16  Object oriented DBMS
Websiteimpala.apache.orgwww.datomic.comwww.transwarp.cn/­en/­product/­stellardbwakanda.github.io
Technical documentationimpala.apache.org/­impala-docs.htmldocs.datomic.comwakanda.github.io/­doc
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCognitectTranswarpWakanda SAS
Initial release201320122012
Current release4.1.0, June 20221.0.7075, December 20232.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infolimited edition freecommercialOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, ClojureC++, JavaScript
Server operating systemsLinuxAll OS with a Java VMLinux
OS X
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.nonono
Secondary indexesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like query languageno
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIOpenCypherRESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCClojure
Java
JavaScript
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infoTransaction Functionsyes
TriggersnoBy using transaction functionsyes
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peershorizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone infoBut extensive use of caching in the application peersnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
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 Kerberosnoyesyes

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More resources
Apache ImpalaDatomicTranswarp StellarDBWakandaDB
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