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DBMS > Apache Druid vs. Apache Impala vs. Databricks vs. GigaSpaces vs. Postgres-XL

System Properties Comparison Apache Druid vs. Apache Impala vs. Databricks vs. GigaSpaces vs. Postgres-XL

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonGigaSpaces  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAnalytic 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 performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSDocument store
Relational DBMS
Document store
Object oriented DBMS infoValues are user defined objects
Relational DBMS
Secondary database modelsDocument storeGraph DBMS
Search engine
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.85
Rank#96  Overall
#50  Relational DBMS
#6  Time Series DBMS
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score0.91
Rank#197  Overall
#33  Document stores
#7  Object oriented DBMS
Score0.43
Rank#260  Overall
#119  Relational DBMS
Websitedruid.apache.orgimpala.apache.orgwww.databricks.comwww.gigaspaces.comwww.postgres-xl.org
Technical documentationdruid.apache.org/­docs/­latest/­designimpala.apache.org/­impala-docs.htmldocs.databricks.comdocs.gigaspaces.com/­latest/­landing.htmlwww.postgres-xl.org/­documentation
DeveloperApache Software Foundation and contributorsApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksGigaspaces Technologies
Initial release20122013201320002014 infosince 2012, originally named StormDB
Current release30.0.0, June 20244.1.0, June 202215.5, September 202010 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2commercialOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Java, C++, .NetC
Server operating systemsLinux
OS X
Unix
LinuxhostedLinux
macOS
Solaris
Windows
Linux
macOS
Data schemeyes infoschema-less columns are supportedyesFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
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.nonoyesno infoXML can be used for describing objects metadatayes infoXML type, but no XML query functionality
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementswith Databricks SQLSQL-99 for query and DML statementsyes infodistributed, parallel query execution
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages supporting JDBC/ODBCPython
R
Scala
.Net
C++
Java
Python
Scala
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesyesuser defined functions
Triggersnonoyes, event driven architectureyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factoryesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceyes infoMap-Reduce pattern can be built with XAP task executorsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDACID infoMVCC
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.nononoyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and roles infobased on Apache Sentry and KerberosRole-based access controlfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache DruidApache ImpalaDatabricksGigaSpacesPostgres-XL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache DruidApache ImpalaDatabricksGigaSpacesPostgres-XL
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