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DBMS > Apache Impala vs. Bangdb vs. Databricks vs. mSQL vs. Solr

System Properties Comparison Apache Impala vs. Bangdb vs. Databricks vs. mSQL vs. Solr

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBangdb  Xexclude from comparisonDatabricks  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopConverged and high performance database for device data, events, time series, document and graphThe 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.mSQL (Mini SQL) is a simple and lightweight RDBMSA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSDocument store
Graph DBMS
Time Series DBMS
Document store
Relational DBMS
Relational DBMSSearch engine
Secondary database modelsDocument storeSpatial DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.27
Rank#167  Overall
#77  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websiteimpala.apache.orgbangdb.comwww.databricks.comhughestech.com.au/­products/­msqlsolr.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmldocs.bangdb.comdocs.databricks.comsolr.apache.org/­resources.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaSachin Sinha, BangDBDatabricksHughes TechnologiesApache Software Foundation
Initial release20132012201319942006
Current release4.1.0, June 2022BangDB 2.0, October 20214.4, October 20219.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoBSD 3commercialcommercial infofree licenses can be providedOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, C++CJava
Server operating systemsLinuxLinuxhostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesschema-freeFlexible 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 dateyesyes: string, long, double, int, geospatial, stream, eventsyesyes 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.nonoyesnoyes
Secondary indexesyesyes infosecondary, composite, nested, reverse, geospatialyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL like support with command line toolwith Databricks SQLA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Java API
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Java
Python
Python
R
Scala
C
C++
Delphi
Java
Perl
PHP
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-reducenouser defined functions and aggregatesnoJava plugins
Triggersnoyes, Notifications (with Streaming only)noyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factor, Knob for CAP (enterprise version only)yesnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyTunable consistency, set CAP knob accordinglyImmediate ConsistencynoneEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes, optimistic concurrency controlyesnoyes
Durability infoSupport for making data persistentyesyes, implements WAL (Write ahead log) as wellyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, run db with in-memory only modenonoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyes (enterprise version only)noyes
More information provided by the system vendor
Apache ImpalaBangdbDatabricksmSQL infoMini SQLSolr
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache ImpalaBangdbDatabricksmSQL infoMini SQLSolr
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