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DBMS > Apache Impala vs. InterSystems Caché vs. Lovefield vs. Teradata Aster

System Properties Comparison Apache Impala vs. InterSystems Caché vs. Lovefield vs. Teradata Aster

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonLovefield  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopA multi-model DBMS and application serverEmbeddable relational database for web apps written in pure JavaScriptPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSKey-value store
Object oriented DBMS
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.29
Rank#293  Overall
#133  Relational DBMS
Websiteimpala.apache.orgwww.intersystems.com/­products/­cachegoogle.github.io/­lovefield
Technical documentationimpala.apache.org/­impala-docs.htmldocs.intersystems.comgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.md
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaInterSystemsGoogleTeradata
Initial release2013199720142005
Current release4.1.0, June 20222018.1.4, May 20202.1.12, February 2017
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaScript
Server operating systemsLinuxAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
server-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinux
Data schemeyesdepending on used data modelyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
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.noyesnoyes infoin Aster File Store
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL-like query language infovia JavaScript builder patternyes
APIs and other access methodsJDBC
ODBC
.NET Client API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Java
JavaScriptC
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesnoR packages
TriggersnoyesUsing read-only observersno
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationnoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infousing MemoryDBno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and rolesnofine grained access rights according to SQL-standard

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More resources
Apache ImpalaInterSystems CachéLovefieldTeradata Aster
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