DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Impala vs. ArcadeDB vs. Atos Standard Common Repository vs. Databricks vs. RDF4J

System Properties Comparison Apache Impala vs. ArcadeDB vs. Atos Standard Common Repository vs. Databricks vs. RDF4J

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonArcadeDB  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonDatabricks  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopFast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewrittenHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSDocument store
Graph DBMS
Key-value store
Time Series DBMS infoin next version
Document store
Key-value store
Document store
Relational DBMS
RDF store
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
Score0.02
Rank#366  Overall
#50  Document stores
#38  Graph DBMS
#53  Key-value stores
#36  Time Series DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websiteimpala.apache.orgarcadedb.comatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.databricks.comrdf4j.org
Technical documentationimpala.apache.org/­impala-docs.htmldocs.arcadedb.comdocs.databricks.comrdf4j.org/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaArcade DataAtos Convergence CreatorsDatabricksSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20132021201620132004
Current release4.1.0, June 2022September 20211703
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaJavaJava
Server operating systemsLinuxAll OS with a Java VMLinuxhostedLinux
OS X
Unix
Windows
Data schemeyesschema-freeSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)yes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesoptionalyes
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.nonoyesyes
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language, no joinsnowith Databricks SQLno
APIs and other access methodsJDBC
ODBC
JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin
LDAPJDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesAll languages supporting JDBC/ODBCJavaAll languages with LDAP bindingsPython
R
Scala
Java
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenouser defined functions and aggregatesyes
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationyesyesnone
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 or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyes inforelationship in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic execution of specific operationsACIDACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosLDAP bind authenticationno
More information provided by the system vendor
Apache ImpalaArcadeDBAtos Standard Common RepositoryDatabricksRDF4J infoformerly known as Sesame
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Apache ImpalaArcadeDBAtos Standard Common RepositoryDatabricksRDF4J infoformerly known as Sesame
DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2023
2 January 2024, Matthias Gelbmann, Paul Andlinger

show all

Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

provided by Google News

Infographic: What makes a Mobile Operator's setup future proof?
10 February 2024, Atos

provided by Google News

Databricks is expanding the scope of its AI investments with second VC fund
21 May 2024, Fortune

Databricks vs. Redshift: Data Platform Comparison
22 May 2024, eWeek

XponentL Data Secures Strategic Investment from Databricks Ventures to Fuel Data Transformation & Generative AI
22 May 2024, Business Wire

5. Databricks
14 May 2024, CNBC

XponentL Data Receives Strategic Investment from Databricks Ventures and Inoca Capital Partners
22 May 2024, FinSMEs

provided by Google News

GraphDB Goes Open Source
27 January 2020, iProgrammer

Ontotext's GraphDB 8.10 Makes Knowledge Graph Experience Faster and Richer
13 June 2019, Markets Insider

provided by Google News



Share this page

Featured Products

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

SingleStore logo

The database to transact, analyze and contextualize your data in real time.
Try it today.

Present your product here