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

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

Editorial information provided by DB-Engines

Name

Description

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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

Primary database model

Relational DBMS

Document store

Relational DBMS

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	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

www.datomic.com

github.com/Softmotions/ejdb

cloud.google.com/bigquery

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

Technical documentation

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

docs.datomic.com

github.com/Softmotions/ejdb/blob/master/README.md

cloud.google.com/bigquery/docs

docs.heavy.ai

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Cognitect

Softmotions

Google

HEAVY.AI, Inc.

Initial release

2016

2012

2010

2016

Current release

1.0.6735, June 2023

5.10, January 2022

License

Commercial or Open Source

commercial

limited edition free

Open Source

GPLv2

commercial

Open Source

Apache Version 2; enterprise edition available

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, Clojure

C++ and CUDA

Server operating systems

hosted

All OS with a Java VM

server-less

hosted

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

in-process shared library

RESTful HTTP/JSON API

JDBC
ODBC
Thrift
Vega

Supported programming languages

C
Java
Perl
Python
R

Clojure
Java

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

user defined functions

in JavaScript

Triggers

yes

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

But extensive use of caching in the application peers

none

Sharding

Round robin

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

But extensive use of caching in the application peers

none

Multi-source replication

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

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

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

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