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DBMS > Ignite vs. Impala

System Properties Comparison Ignite vs. Impala

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Editorial information provided by DB-Engines
NameIgnite  Xexclude from comparisonImpala  Xexclude from comparison
DescriptionApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Analytic DBMS for Hadoop
Primary database modelKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.49
Rank#76  Overall
#11  Key-value stores
#42  Relational DBMS
Score19.56
Rank#36  Overall
#22  Relational DBMS
Websiteignite.apache.orgwww.cloudera.com/­products/­open-source/­apache-hadoop/­impala.html
Technical documentationapacheignite.readme.io/­docsdocs.cloudera.com/­documentation/­enterprise/­latest/­topics/­impala.html
DeveloperApache Software FoundationCloudera
Initial release20152013
Current releaseApache Ignite 2.63.4.0, April 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, Java, .NetC++
Server operating systemsLinux
OS X
Solaris
Windows
Linux
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
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.yesno
Secondary indexesyesyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statements
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBC
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)yes infouser defined functions and integration of map-reduce
Triggersyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)yes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlSecurity Hooks for custom implementationsAccess rights for users, groups and roles infobased on Apache Sentry and Kerberos

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More resources
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