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

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

Editorial information provided by DB-Engines

Name

Description

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

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

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

Open Source Time Series DBMS

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.76
Rank	#220	Overall
	#102	Relational DBMS

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

geode.apache.org

cloud.google.com/bigquery

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

siridb.com

Technical documentation

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

geode.apache.org/docs

cloud.google.com/bigquery/docs

docs.heavy.ai

docs.siridb.com

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Google

HEAVY.AI, Inc.

Cesbit

Initial release

2016

2002

2010

2016

2017

Current release

1.1, February 2017

5.10, January 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

MIT License

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

Java

C++ and CUDA

Server operating systems

hosted

All OS with a Java VM

the JDK (8 or later) is also required

hosted

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data

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

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (OQL)

yes

APIs and other access methods

JDBC
ODBC

Java Client API
Memcached protocol
RESTful HTTP API

RESTful HTTP/JSON API

JDBC
ODBC
Thrift
Vega

HTTP API

Supported programming languages

C
Java
Perl
Python
R

.Net
All JVM based languages
C++
Groovy
Java
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Sharding

Round robin

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

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 rights per client and object definable

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

simple rights management via user accounts

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