DBMS > BigchainDB vs. GBase vs. HEAVY.AI vs. Snowflake

System Properties Comparison BigchainDB vs. GBase vs. HEAVY.AI vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Document store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.bigchaindb.com

www.gbase.cn

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

www.snowflake.com

Technical documentation

bigchaindb.readthedocs.io/en/latest

docs.heavy.ai

docs.snowflake.net/manuals/index.html

Developer

General Data Technology Co., Ltd.

HEAVY.AI, Inc.

Snowflake Computing Inc.

Initial release

2016

2004

2016

2014

Current release

GBase 8a, GBase 8s, GBase 8c

5.10, January 2022

License

Commercial or Open Source

Open Source

AGPL v3

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

Python

C, Java, Python

C++ and CUDA

Server operating systems

Linux

hosted

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

Secondary indexes

yes

SQL

Support of SQL

Standard with numerous extensions

yes

APIs and other access methods

CLI Client
RESTful HTTP API

ADO.NET
C API
JDBC
ODBC

JDBC
ODBC
Thrift
Vega

CLI Client
JDBC
ODBC

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

Round robin

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

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

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

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

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

yes

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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