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DBMS > Apache Impala vs. Fujitsu Enterprise Postgres vs. Sphinx vs. Teradata Aster

System Properties Comparison Apache Impala vs. Fujitsu Enterprise Postgres vs. Sphinx vs. Teradata Aster

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonSphinx  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Open source search engine for searching in data from different sources, e.g. relational databasesPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSRelational DBMSSearch engineRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websiteimpala.apache.orgwww.postgresql.fastware.comsphinxsearch.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.postgresql.fastware.com/­product-manualssphinxsearch.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaPostgreSQL Global Development Group, Fujitsu Australia Software TechnologySphinx Technologies Inc.Teradata
Initial release201320012005
Current release4.1.0, June 2022Fujitsu Enterprise Postgres 14, January 20223.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoGPL version 2, commercial licence availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CC++
Server operating systemsLinuxLinux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeyesyesyesFlexible 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 dateyesyesnoyes
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 Store
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL-like query language (SphinxQL)yes
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Proprietary protocolADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsnoR packages
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and by hashSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
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 integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
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-standardnofine grained access rights according to SQL-standard
More information provided by the system vendor
Apache ImpalaFujitsu Enterprise PostgresSphinxTeradata Aster
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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More resources
Apache ImpalaFujitsu Enterprise PostgresSphinxTeradata Aster
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