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DBMS > Apache Impala vs. Brytlyt vs. EJDB vs. QuestDB vs. RDFox

System Properties Comparison Apache Impala vs. Brytlyt vs. EJDB vs. QuestDB vs. RDFox

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBrytlyt  Xexclude from comparisonEJDB  Xexclude from comparisonQuestDB  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)A high performance open source SQL database for time series dataHigh performance knowledge graph and semantic reasoning engine
Primary database modelRelational DBMSRelational DBMSDocument storeTime Series DBMSGraph DBMS
RDF store
Secondary database modelsDocument storeRelational DBMSRelational 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
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Score0.29
Rank#300  Overall
#24  Graph DBMS
#13  RDF stores
Websiteimpala.apache.orgbrytlyt.iogithub.com/­Softmotions/­ejdbquestdb.iowww.oxfordsemantic.tech
Technical documentationimpala.apache.org/­impala-docs.htmldocs.brytlyt.iogithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdquestdb.io/­docsdocs.oxfordsemantic.tech
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaBrytlytSoftmotionsQuestDB Technology IncOxford Semantic Technologies
Initial release20132016201220142017
Current release4.1.0, June 20225.0, August 20236.0, Septermber 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoGPLv2Open Source infoApache 2.0commercial
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 CUDACJava (Zero-GC), C++, RustC++
Server operating systemsLinuxLinux
OS X
Windows
server-lessLinux
macOS
Windows
Linux
macOS
Windows
Data schemeyesyesschema-freeyes infoschema-free via InfluxDB Line Protocolyes 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 statementsyesnoSQL with time-series extensionsno
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
in-process shared libraryHTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
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 infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
C
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions infoin PL/pgSQLnono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationnoneSource-replica replication with eventual consistencyreplication 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 ConsistencyImmediate 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 datanoACIDnoACID for single-table writesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoRead/Write Lockingyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infothrough memory mapped filesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardnoRoles, resources, and access types
More information provided by the system vendor
Apache ImpalaBrytlytEJDBQuestDBRDFox
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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More resources
Apache ImpalaBrytlytEJDBQuestDBRDFox
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