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DBMS > Amazon Redshift vs. Apache Impala vs. ArcadeDB vs. Databricks vs. Infobright

System Properties Comparison Amazon Redshift vs. Apache Impala vs. ArcadeDB vs. Databricks vs. Infobright

Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonApache Impala  Xexclude from comparisonArcadeDB  Xexclude from comparisonDatabricks  Xexclude from comparisonInfobright  Xexclude from comparison
DescriptionLarge scale data warehouse service for use with business intelligence toolsAnalytic DBMS for HadoopFast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewrittenThe 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.High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend
Primary database modelRelational DBMSRelational DBMSDocument store
Graph DBMS
Key-value store
Time Series DBMS infoin next version
Document store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score17.94
Rank#34  Overall
#21  Relational DBMS
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
Score0.96
Rank#194  Overall
#91  Relational DBMS
Websiteaws.amazon.com/­redshiftimpala.apache.orgarcadedb.comwww.databricks.comignitetech.com/­softwarelibrary/­infobrightdb
Technical documentationdocs.aws.amazon.com/­redshiftimpala.apache.org/­impala-docs.htmldocs.arcadedb.comdocs.databricks.com
DeveloperAmazon (based on PostgreSQL)Apache Software Foundation infoApache top-level project, originally developed by ClouderaArcade DataDatabricksIgnite Technologies Inc.; formerly InfoBright Inc.
Initial release20122013202120132005
Current release4.1.0, June 2022September 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoApache Version 2.0commercialcommercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++JavaC
Server operating systemshostedLinuxAll OS with a Java VMhostedLinux
Windows
Data schemeyesyesschema-freeFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nononoyesno
Secondary indexesrestrictedyesyesyesno infoKnowledge Grid Technology used instead
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardSQL-like DML and DDL statementsSQL-like query language, no joinswith Databricks SQLyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCAll languages supporting JDBC/ODBCJavaPython
R
Scala
.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions infoin Pythonyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesno
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorSource-replica replicationyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnoyes inforelationship in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesnonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilities
More information provided by the system vendor
Amazon RedshiftApache ImpalaArcadeDBDatabricksInfobright
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon RedshiftApache ImpalaArcadeDBDatabricksInfobright
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