DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Bangdb vs. EsgynDB vs. Teradata Aster vs. TerarkDB

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Bangdb vs. EsgynDB vs. Teradata Aster vs. TerarkDB

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

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

Converged and high performance database for device data, events, time series, document and graph

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Platform for big data analytics on multistructured data sources and types

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Relational DBMS

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

www.alibabacloud.com/product/hybriddb-postgresql

bangdb.com

www.esgyn.cn

github.com/bytedance/terarkdb

Technical documentation

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

docs.bangdb.com

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Sachin Sinha, BangDB

Esgyn

Teradata

ByteDance, originally Terark

Initial release

2016

2012

2015

2005

2016

Current release

BangDB 2.0, October 2021

License

Commercial or Open Source

commercial

Open Source

BSD 3

commercial

restricted open source version 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

C, C++

C++, Java

C++

Server operating systems

hosted

Linux

Data scheme

yes

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

schema-free

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

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

in Aster File Store

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

yes

SQL like support with command line tool

yes

APIs and other access methods

JDBC
ODBC

Proprietary protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

C++ API
Java API

Supported programming languages

C
Java
Perl
Python
R

C
C#
C++
Java
Python

All languages supporting JDBC/ODBC/ADO.Net

C
C#
C++
Java
Python
R

C++
Java

Server-side scripts

Stored procedures

yes

Java Stored Procedures

R packages

Triggers

yes

yes, Notifications (with Streaming only)

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor, Knob for CAP (enterprise version only)

Multi-source replication between multi datacenters

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes (enterprise version only)

fine grained access rights according to SQL-standard

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