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DBMS > Apache Impala vs. Brytlyt vs. EJDB vs. IBM Db2 Event Store vs. RDFox

System Properties Comparison Apache Impala vs. Brytlyt vs. EJDB vs. IBM Db2 Event Store vs. RDFox

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBrytlyt  Xexclude from comparisonEJDB  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonRDFox  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Distributed Event Store optimized for Internet of Things use casesHigh performance knowledge graph and semantic reasoning engine
Primary database modelRelational DBMSRelational DBMSDocument storeEvent Store
Time Series DBMS
Graph DBMS
RDF store
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.38
Rank#276  Overall
#127  Relational DBMS
Score0.31
Rank#296  Overall
#44  Document stores
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.29
Rank#300  Overall
#24  Graph DBMS
#13  RDF stores
Websiteimpala.apache.orgbrytlyt.iogithub.com/­Softmotions/­ejdbwww.ibm.com/­products/­db2-event-storewww.oxfordsemantic.tech
Technical documentationimpala.apache.org/­impala-docs.htmldocs.brytlyt.iogithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdwww.ibm.com/­docs/­en/­db2-event-storedocs.oxfordsemantic.tech
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaBrytlytSoftmotionsIBMOxford Semantic Technologies
Initial release20132016201220172017
Current release4.1.0, June 20225.0, August 20232.06.0, Septermber 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoGPLv2commercial infofree developer edition availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, C++ and CUDACC and C++C++
Server operating systemsLinuxLinux
OS X
Windows
server-lessLinux infoLinux, macOS, Windows for the developer additionLinux
macOS
Windows
Data schemeyesyesschema-freeyesyes infoRDF schemas
Typing infopredefined data types such as float or dateyesyesyes infostring, integer, double, bool, date, object_idyesyes
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 functionality.no
Secondary indexesyesyesnono
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnoyes infothrough the embedded Spark runtimeno
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
in-process shared libraryADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
RESTful HTTP API
SPARQL 1.1
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
Perl
Python
Tcl
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions infoin PL/pgSQLnoyes
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationnoneActive-active shard replicationreplication via a shared file system
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setups
Foreign keys infoReferential integritynoyesno infotypically not needed, however similar functionality with collection joins possibleno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoRead/Write LockingNo - written data is immutable
Durability infoSupport for making data persistentyesyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standardRoles, resources, and access types

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More resources
Apache ImpalaBrytlytEJDBIBM Db2 Event StoreRDFox
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