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DBMS > Apache Impala vs. Drizzle vs. Quasardb vs. STSdb vs. Teradata Aster

System Properties Comparison Apache Impala vs. Drizzle vs. Quasardb vs. STSdb vs. Teradata Aster

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDrizzle  Xexclude from comparisonQuasardb  Xexclude from comparisonSTSdb  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded 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 HadoopMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Distributed, high-performance timeseries databaseKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSRelational DBMSTime Series DBMSKey-value storeRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websiteimpala.apache.orgquasar.aigithub.com/­STSSoft/­STSdb4
Technical documentationimpala.apache.org/­impala-docs.htmldoc.quasar.ai/­master
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDrizzle project, originally started by Brian AkerquasardbSTS Soft SCTeradata
Initial release20132008200920112005
Current release4.1.0, June 20227.2.4, September 20123.14.1, January 20244.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGNU GPLcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoGPLv2, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C++C#
Server operating systemsLinuxFreeBSD
Linux
OS X
BSD
Linux
OS X
Windows
WindowsLinux
Data schemeyesyesschema-freeyesFlexible 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 dateyesyesyes infointeger and binaryyes infoprimitive types and user defined types (classes)yes
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.nonoyes infoin Aster File Store
Secondary indexesyesyesyes infowith tagsnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infowith proprietary extensionsSQL-like query languagenoyes
APIs and other access methodsJDBC
ODBC
JDBCHTTP API.NET Client APIADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Java
PHP
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C#
Java
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenononoR packages
Triggersnono infohooks for callbacks inside the server can be used.nonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoconsistent hashingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
Source-replica replication with selectable replication factornoneyes 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 MapReducenowith Hadoop integrationnoyes 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 integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient modeno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosPluggable authentication mechanisms infoe.g. LDAP, HTTPCryptographically strong user authentication and audit trailnofine grained access rights according to SQL-standard

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More resources
Apache ImpalaDrizzleQuasardbSTSdbTeradata Aster
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