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DBMS > Apache Impala vs. CrateDB vs. Quasardb vs. RDF4J

System Properties Comparison Apache Impala vs. CrateDB vs. Quasardb vs. RDF4J

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonCrateDB  Xexclude from comparisonQuasardb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDistributed Database based on LuceneDistributed, high-performance timeseries databaseRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Time Series DBMSRDF 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
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#10  Vector DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Websiteimpala.apache.orgcratedb.comquasar.airdf4j.org
Technical documentationimpala.apache.org/­impala-docs.htmlcratedb.com/­docsdoc.quasar.ai/­masterrdf4j.org/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCratequasardbSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2013201320092004
Current release4.1.0, June 20223.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Sourcecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++Java
Server operating systemsLinuxAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportBSD
Linux
OS X
Windows
Linux
OS X
Unix
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesyes infointeger and binaryyes
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 indexesyesyesyes infowith tagsyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-like query languageno
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesAll languages supporting JDBC/ODBC.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions (Javascript)noyes
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoconsistent hashingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorConfigurable replication on table/partition-levelSource-replica replication with selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenowith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Read-after-write consistency on record level
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infounique row identifiers can be used for implementing an optimistic concurrency control strategyACIDACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoTransient mode
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosrights management via user accountsCryptographically strong user authentication and audit trailno

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Apache ImpalaCrateDBQuasardbRDF4J infoformerly known as Sesame
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