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

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonSolr  Xexclude from comparisonTibero  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.A widely used distributed, scalable search engine based on Apache LuceneA secure RDBMS, designed for easy portability from Oracle
Primary database modelRelational DBMSDocument store
Relational DBMS
Search engineRelational DBMS
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score1.78
Rank#140  Overall
#64  Relational DBMS
Websiteimpala.apache.orgwww.databricks.comsolr.apache.orgus.tmaxsoft.com/­products/­tibero
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comsolr.apache.org/­resources.htmltechnet.tmaxsoft.com/­upload/­download/­online/­tibero/­pver-20150504-000002/­index.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksApache Software FoundationTmaxSoft
Initial release2013201320062003
Current release4.1.0, June 20229.6.0, April 20246, April 2015
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC and Assembler
Server operating systemsLinuxhostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)AIX
HP-UX
Linux
Solaris
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes infosupports customizable data types and automatic typingyes
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.noyesyesyes
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLSolr Parallel SQL Interfaceyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesJava pluginsPersistent Stored Procedure (PSM)
Triggersnoyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning infoby range, hash, list or composite
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducespark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic lockingACID
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.nonoyesno infoplanned for next version
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyesfine grained access rights according to SQL-standard (SQL 92, SQL 99)
More information provided by the system vendor
Apache ImpalaDatabricksSolrTibero
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache ImpalaDatabricksSolrTibero
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