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DBMS > Apache Impala vs. Teradata Aster vs. Yaacomo

System Properties Comparison Apache Impala vs. Teradata Aster vs. Yaacomo

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonTeradata Aster  Xexclude from comparisonYaacomo  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionAnalytic DBMS for HadoopPlatform for big data analytics on multistructured data sources and typesOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Websiteimpala.apache.orgyaacomo.com
Technical documentationimpala.apache.org/­impala-docs.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaTeradataQ2WEB GmbH
Initial release201320052009
Current release4.1.0, June 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++
Server operating systemsLinuxLinuxAndroid
Linux
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeyes
Typing infopredefined data types such as float or dateyesyesyes
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 infoin Aster File Storeno
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyes
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceR packages
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infoSQL Map-Reduce Frameworkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache ImpalaTeradata AsterYaacomo
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