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DBMS > Apache Impala vs. Postgres-XL vs. XTDB

System Properties Comparison Apache Impala vs. Postgres-XL vs. XTDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonPostgres-XL  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelRelational DBMSRelational DBMSDocument store
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.57
Rank#40  Overall
#24  Relational DBMS
Score0.46
Rank#258  Overall
#120  Relational DBMS
Score0.12
Rank#337  Overall
#46  Document stores
Websiteimpala.apache.orgwww.postgres-xl.orggithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.postgres-xl.org/­documentationwww.xtdb.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaJuxt Ltd.
Initial release20132014 infosince 2012, originally named StormDB2019
Current release4.1.0, June 202210 R1, October 20181.19, September 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoMozilla public licenseOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CClojure
Server operating systemsLinuxLinux
macOS
All OS with a Java 8 (and higher) VM
Linux
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes, extensible-data-notation format
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 infoXML type, but no XML query functionalityno
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infodistributed, parallel query executionlimited SQL, making use of Apache Calcite
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP REST
JDBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Clojure
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsno
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoMVCCACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standard

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More resources
Apache ImpalaPostgres-XLXTDB infoformerly named Crux
Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

How different SQL-on-Hadoop engines satisfy BI workloads
24 February 2016, CIO

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News



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