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

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Document store
Spatial DBMS
Time Series DBMS
Vector 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
Score4.12
Rank#70  Overall
#38  Relational DBMS
Websiteimpala.apache.orgwww.postgres-xl.orgwww.singlestore.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.postgres-xl.org/­documentationdocs.singlestore.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaSingleStore Inc.
Initial release20132014 infosince 2012, originally named StormDB2013
Current release4.1.0, June 202210 R1, October 20188.5, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoMozilla public licensecommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CC++, Go
Server operating systemsLinuxLinux
macOS
Linux info64 bit version required
Data schemeyesyesyes
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 infoXML type, but no XML query functionalityno
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infodistributed, parallel query executionyes infobut no triggers and foreign keys
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Bash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsyes
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningSharding infohash partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replication infostores two copies of each physical data partition on two separate nodes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono infocan define user-defined aggregate functions for map-reduce-style calculations
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate 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, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.
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 control via users, groups and roles
More information provided by the system vendor
Apache ImpalaPostgres-XLSingleStore infoformer name was MemSQL
Specific characteristicsSingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more
Competitive advantagesSingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more
Typical application scenariosDriving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more
Key customersIEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more
Market metricsCustomers in various industries worldwide including US and International Industry...
» more
Licensing and pricing modelsF ree Tier and Enterprise Edition
» more

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More resources
Apache ImpalaPostgres-XLSingleStore infoformer name was MemSQL
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