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DBMS > Apache Impala vs. Databricks vs. Infobright vs. Solr

System Properties Comparison Apache Impala vs. Databricks vs. Infobright vs. Solr

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonInfobright  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopThe 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 frontendA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMSSearch engine
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.02
Rank#192  Overall
#90  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websiteimpala.apache.orgwww.databricks.comignitetech.com/­softwarelibrary/­infobrightdbsolr.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comsolr.apache.org/­resources.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksIgnite Technologies Inc.; formerly InfoBright Inc.Apache Software Foundation
Initial release2013201320052006
Current release4.1.0, June 20229.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CJava
Server operating systemsLinuxhostedLinux
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typing
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.noyesnoyes
Secondary indexesyesyesno infoKnowledge Grid Technology used insteadyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLyesSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
Java API
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesnoJava plugins
Triggersnonoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilitiesyes
More information provided by the system vendor
Apache ImpalaDatabricksInfobrightSolr
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache ImpalaDatabricksInfobrightSolr
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