DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Amazon Redshift vs. HEAVY.AI vs. Hive vs. PostgreSQL
System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Amazon Redshift vs. HEAVY.AI vs. Hive vs. PostgreSQL
| Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Name | Alibaba Cloud AnalyticDB for PostgreSQL  former name was HybridDB Xexclude from comparison | Amazon Redshift Xexclude from comparison | HEAVY.AI Formerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022 Xexclude from comparison | Hive Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum | Large scale data warehouse service for use with business intelligence tools | A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware | data warehouse software for querying and managing large distributed datasets, built on Hadoop | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Relational DBMS | Relational DBMS | Relational DBMS | Relational DBMS | 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 | Spatial DBMS | Document store Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|
|
|
|
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Website | www.alibabacloud.com/product/hybriddb-postgresql | aws.amazon.com/redshift | github.com/heavyai/heavydb www.heavy.ai | hive.apache.org | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview | docs.aws.amazon.com/redshift | docs.heavy.ai | cwiki.apache.org/confluence/display/Hive/Home | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group | Amazon (based on PostgreSQL) | HEAVY.AI, Inc. | Apache Software Foundation initially developed by Facebook | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2016 | 2012 | 2016 | 2012 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 5.10, January 2022 | 3.1.3, April 2022 | 16.3, May 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial | commercial | Open Source Apache Version 2; enterprise edition available | Open Source Apache Version 2 | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | yes | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. |
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Implementation language | C | C++ and CUDA | Java | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | hosted | hosted | Linux | All OS with a Java VM | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | yes | yes | yes | 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. | yes | no | no | yes specific XML-type available, but no XML query functionality. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | restricted | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | yes | yes does not fully support an SQL-standard | yes | SQL-like DML and DDL statements | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | JDBC ODBC | JDBC ODBC | JDBC ODBC Thrift Vega | JDBC ODBC Thrift | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | C Java Perl Python R | All languages supporting JDBC/ODBC | All languages supporting JDBC/ODBC/Thrift Python | C++ Java PHP Python | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | yes | user defined functions in Python | no | yes user defined functions and integration of map-reduce | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes | no | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Sharding Implicit feature of the cloud service | Sharding | Sharding Round robin | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | yes Implicit feature of the cloud service | yes | Multi-source replication | selectable replication factor | Source-replica replication other methods possible by using 3rd party extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | no | no | no | yes query execution via MapReduce | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate Consistency | Immediate Consistency | Eventual Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | yes | yes informational only, not enforced by the system | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | ACID | no | no | 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 | fine grained access rights according to SQL-standard | fine grained access rights according to SQL-standard | fine grained access rights according to SQL-standard | Access rights for users, groups and roles | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendorWe invite representatives of system vendors to contact us for updating and extending the system information, | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Related products and services | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 3rd parties | CData: Connect to Big Data & NoSQL through standard Drivers. » more | Timescale: Calling all PostgreSQL users – the 2023 State of PostgreSQL survey is now open! Share your favorite extensions, preferred frameworks, community experiences, and more. Take the survey today!
» more Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools. » more Fujitsu Enterprise Postgres: An Enterprise Grade PostgreSQL with the flexibility of a hybrid cloud solution combined with industry leading security, availability and performance. » more pgDash: In-Depth PostgreSQL Monitoring. » more Navicat Monitor is a safe, simple and agentless remote server monitoring tool for PostgreSQL and many other database management systems. » more SharePlex is the reliable and affordable data replication solution for PostgreSQL migrations, high availability and more. » more CYBERTEC is your professional partner in PostgreSQL topics for over 20 years. As our main aim is to be your single-source all-in-one IT service provider, we offer a wide range of products and services. Visit our website for more details. » more Navicat for PostgreSQL is an easy-to-use graphical tool for PostgreSQL database development. » more Instaclustr: Fully Hosted & Managed PostgreSQL » more Redgate webinars: A series of key topics for new PostgreSQL users. » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
We invite representatives of vendors of related products to contact us for presenting information about their offerings here. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Alibaba Cloud AnalyticDB for PostgreSQL former name was HybridDB | Amazon Redshift | HEAVY.AI Formerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022 | Hive | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DB-Engines blog posts | Cloud-based DBMS's popularity grows at high rates The popularity of cloud-based DBMSs has increased tenfold in four years Increased popularity for consuming DBMS services out of the cloud | Why is Hadoop not listed in the DB-Engines Ranking? | 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 Two Critical Flaws Found in Alibaba Cloud's PostgreSQL Databases Alibaba Cloud Unveils Database Update for Generative AI Alibaba Cloud to spur AI innovation with upcoming Singapore hackathon in March | KrASIA How Data Analytics Capabilities of Alibaba Group Evolve Its Ecosystem to the Cloud Alibaba Cloud Named a Leader in Gartner(R) Magic Quadrant(TM) for Cloud Database Management Systems provided by Google News Transforming the Member Experience Using Amazon Redshift with Together Credit Union | Case Study Amazon Redshift adds new AI capabilities, including Amazon Q, to boost efficiency and productivity | Amazon Web ... Achieve peak performance and boost scalability using multiple Amazon Redshift serverless workgroups and Network ... Breaking barriers in geospatial: Amazon Redshift, CARTO, and H3 | Amazon Web Services Revolutionizing data querying: Amazon Redshift and Visual Studio Code integration | Amazon Web Services provided by Google News 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 OmniSci Gets HEAVY New Name and New CEO The insideBIGDATA IMPACT 50 List for Q4 2023 provided by Google News Apache Software Foundation Announces Apache® Hive 4.0 ASF Unveils the Next Evolution of Big Data Processing With the Launch of Hive 4.0 Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services 18 Top Big Data Tools and Technologies to Know About in 2024 DataCentral: Uber's Observability and Chargeback Platform provided by Google News Enterprise DB begins rolling AI features into PostgreSQL How LeadSquared accelerated chatbot deployments with generative AI using Amazon Bedrock and Amazon Aurora ... Nutanix partners with EDB to fit database service for AI – Blocks and Files How to Import CSV Data Into PostgreSQL Using Spring Boot Batch EDB unveils EDB Postgres AI provided by Google News | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Share this page
