DBMS > Apache Impala vs. Apache Jena - TDB vs. HEAVY.AI vs. Informix vs. PostgreSQL
System Properties Comparison Apache Impala vs. Apache Jena - TDB vs. HEAVY.AI vs. Informix vs. PostgreSQL
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| Name | Apache Impala Xexclude from comparison | Apache Jena - TDB Xexclude from comparison | HEAVY.AI  Formerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022 Xexclude from comparison | Informix Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | Analytic DBMS for Hadoop | A RDF storage and query DBMS, shipped as an optional-use component of the Apache Jena framework | A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware | A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Relational DBMS | RDF store | Relational DBMS | Relational DBMS Since Version 12.10 support for JSON/BSON datatypes compatible with MongoDB | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Document store | Spatial DBMS | Document store Spatial DBMS Time Series DBMS with Informix TimeSeries Extension | Document store Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | impala.apache.org | jena.apache.org/documentation/tdb/index.html | github.com/heavyai/heavydb www.heavy.ai | www.ibm.com/products/informix | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | impala.apache.org/impala-docs.html | jena.apache.org/documentation/tdb/index.html | docs.heavy.ai | informix.hcldoc.com www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Apache Software Foundation Apache top-level project, originally developed by Cloudera | Apache Software Foundation originally developed by HP Labs | HEAVY.AI, Inc. | IBM, HCL Technologies Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales. | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2013 | 2000 | 2016 | 1984 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 4.1.0, June 2022 | 4.9.0, July 2023 | 5.10, January 2022 | 14.10.FC5, November 2020 | 16.3, May 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | Open Source Apache Version 2 | Open Source Apache License, Version 2.0 | Open Source Apache Version 2; enterprise edition available | commercial free developer edition available | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Implementation language | C++ | Java | C++ and CUDA | C, C++ and Java | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | Linux | All OS with a Java VM | Linux | AIX HP-UX Linux macOS Solaris Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | yes | yes RDF Schemas | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | yes | yes | yes Since Version 12.10 support for JSON/BSON datatypes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT. | no | no | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | yes | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | SQL-like DML and DDL statements | no | yes | yes | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | JDBC ODBC | Fuseki REST-style SPARQL HTTP Interface Jena RDF API RIO RDF Input/Output | JDBC ODBC Thrift Vega | JDBC JSON API MongoDB compatibleMQTT (Message Queue Telemetry Transport) ODBC RESTful HTTP API | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | All languages supporting JDBC/ODBC | Java | All languages supporting JDBC/ODBC/Thrift Python | .Net C C++ Java JavaScript (Node.js) PHP Python Ruby | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | yes user defined functions and integration of map-reduce | yes | no | yes | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | no | yes via event handler | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Sharding | none | Sharding Round robin | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | selectable replication factor | none | Multi-source replication | Multi-source replication Source-replica replication | Source-replica replication other methods possible by using 3rd party extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | yes query execution via MapReduce | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency | Immediate Consistency | Immediate Consistency | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | no | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | ACID TDB Transactions | no | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | yes | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | Access rights for users, groups and roles based on Apache Sentry and Kerberos | Access control via Jena Security | fine grained access rights according to SQL-standard | Users with fine-grained authentication, authorization, and auditing controls | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Apache Impala | Apache Jena - TDB | HEAVY.AI Formerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022 | Informix | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DB-Engines blog posts | PostgreSQL is the DBMS of the Year 2023 Snowflake is the DBMS of the Year 2022, defending the title from last year Snowflake is the DBMS of the Year 2021 Monitoring PostgreSQL with Redgate Monitor Apache Impala becomes Top-Level Project Cloudera Bringing Impala to AWS Cloud Apache Doris just 'graduated': Why care about this SQL data warehouse Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop Updates & Upserts in Hadoop Ecosystem with Apache Kudu provided by Google News Sparql Secrets In Jena-Fuseki - DataScienceCentral.com A catalogue with semantic annotations makes multilabel datasets FAIR | Scientific Reports MarkLogic Hones Its Triple Store Comparing Grakn to Semantic Web Technologies — Part 1/3 | by Tomas Sabat How relevant is data analytics to businesses today? provided by Google News HEAVY.AI Introduces HeavyIQ, Delivering Powerful Conversational Analytics Focused on Location and Time Data Big Data Analytics: A Game Changer for Infrastructure HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities Making the most of geospatial intelligence The insideBIGDATA IMPACT 50 List for Q4 2023 provided by Google News Unlock the value of your Informix data for advanced analytics and AI with watsonx.data IBM Informix: A key part of IBM’s hybrid cloud and AI strategy IBM Unleashes 'Cheetah' Database IBM Informix review: What you need to know about the software IBM Informix Database in the Cloud | AWS News Blog provided by Google News ServiceNow trades MariaDB for RaptorDB (PostgreSQL) AGEDB Technology Launches PGTS - PostgreSQL Tech-Support First Principles: Optimizing PostgreSQL for the cloud Automatically Generate Types for Your PostgreSQL Database General availability: Microsoft Entra ID integration with Azure Cosmos DB for PostgreSQL | Azure updates provided by Google News | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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