DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Google BigQuery vs. HEAVY.AI vs. Interbase

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Google BigQuery vs. HEAVY.AI vs. Interbase

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

Large scale data warehouse service with append-only tables

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Light-weight proven RDBMS

originally from Borland

Primary database model

Relational DBMS

Secondary database models

Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.62
Rank	#241	Overall
	#110	Relational DBMS

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	5.04
Rank	#71	Overall
	#39	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

cloud.google.com/bigquery

github.com/heavyai/heavydb
www.heavy.ai

www.embarcadero.com/products/interbase

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

cloud.google.com/bigquery/docs

docs.heavy.ai

docs.embarcadero.com/products/interbase

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Google

HEAVY.AI, Inc.

Embarcadero

Initial release

2016

2010

2016

1984

Current release

5.10, January 2022

InterBase 2020, December 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++ and CUDA

Server operating systems

hosted

Linux

Android
iOS
Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

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

export as XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
ODBC

RESTful HTTP/JSON API

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
ODBC

Supported programming languages

C
Java
Perl
Python
R

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

yes

Interbase procedure and trigger language

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication

Interbase Change Views

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.