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DBMS > Apache Impala vs. GridGain vs. Ultipa

System Properties Comparison Apache Impala vs. GridGain vs. Ultipa

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGridGain  Xexclude from comparisonUltipa  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopGridGain is an in-memory computing platform, built on Apache IgniteHigh performance Graph DBMS supporting HTAP high availability cluster deployment
Primary database modelRelational DBMSColumnar
Key-value store
Object oriented DBMS
Relational DBMS
Graph DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score1.48
Rank#150  Overall
#1  Columnar
#26  Key-value stores
#2  Object oriented DBMS
#69  Relational DBMS
Score0.11
Rank#338  Overall
#32  Graph DBMS
Websiteimpala.apache.orgwww.gridgain.comwww.ultipa.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.gridgain.com/­docs/­index.htmlwww.ultipa.com/­document
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGridGain Systems, Inc.Ultipa
Initial release201320072019
Current release4.1.0, June 2022GridGain 8.5.1
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial, open sourcecommercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, C++, .Net, Python, REST, SQL
Server operating systemsLinuxLinux
OS X
Solaris
Windows
z/OS
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.noyes
Secondary indexesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsJDBC
ODBC
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Java
PHP
Python
Ruby
Scala
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes (compute grid and cache interceptors can be used instead)
Triggersnoyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes (compute grid and hadoop accelerator)
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
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.noyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosRole-based access control
Security Hooks for custom implementations

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More resources
Apache ImpalaGridGainUltipa
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