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DBMS > Apache Impala vs. Fujitsu Enterprise Postgres vs. Solr vs. Stardog

System Properties Comparison Apache Impala vs. Fujitsu Enterprise Postgres vs. Solr vs. Stardog

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonSolr  Xexclude from comparisonStardog  Xexclude from comparison
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.A widely used distributed, scalable search engine based on Apache LuceneEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMSRelational DBMSSearch engineGraph DBMS
RDF store
Secondary database modelsDocument storeDocument store
Spatial DBMS
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
Score42.91
Rank#24  Overall
#3  Search engines
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websiteimpala.apache.orgwww.postgresql.fastware.comsolr.apache.orgwww.stardog.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.postgresql.fastware.com/­product-manualssolr.apache.org/­resources.htmldocs.stardog.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyApache Software FoundationStardog-Union
Initial release201320062010
Current release4.1.0, June 2022Fujitsu Enterprise Postgres 14, January 20229.6.0, April 20247.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache Version 2commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CJavaJava
Server operating systemsLinuxLinux
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
macOS
Windows
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingyes
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.noyesno infoImport/export of XML data possible
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSolr Parallel SQL InterfaceYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
RESTful HTTP/JSON API
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsJava pluginsuser defined functions and aggregates, HTTP Server extensions in Java
Triggersnoyesyes infoUser configurable commands triggered on index changesyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and by hashShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationyesMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynoyesnoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardyesAccess rights for users and roles
More information provided by the system vendor
Apache ImpalaFujitsu Enterprise PostgresSolrStardog
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 PostgresSolrStardog
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