DBMS > Bangdb vs. BigchainDB vs. Kinetica vs. Snowflake vs. TerarkDB

System Properties Comparison Bangdb vs. BigchainDB vs. Kinetica vs. Snowflake vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

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

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

Fully vectorized database across both GPUs and CPUs

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

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

Document store
Graph DBMS
Time Series DBMS

Document store

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS

Spatial DBMS
Time Series DBMS

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

Score	0.07
Rank	#346	Overall
	#47	Document stores
	#35	Graph DBMS
	#32	Time Series DBMS

Score	0.76
Rank	#216	Overall
	#36	Document stores

Score	0.42
Rank	#261	Overall
	#120	Relational DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Website

github.com/bytedance/terarkdb

Technical documentation

docs.bangdb.com

bigchaindb.readthedocs.io/en/latest

docs.kinetica.com

docs.snowflake.net/manuals/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Sachin Sinha, BangDB

Kinetica

Snowflake Computing Inc.

ByteDance, originally Terark

Initial release

2012

2016

2012

2014

2016

Current release

BangDB 2.0, October 2021

7.1, August 2021

License

Commercial or Open Source

Open Source

BSD 3

Open Source

AGPL v3

commercial

restricted open source version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Python

C, C++

C++

Server operating systems

Linux

hosted

Data scheme

schema-free

yes

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

schema-free

Typing

predefined data types such as float or date

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

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

SQL-like DML and DDL statements

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

CLI Client
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

C++ API
Java API

Supported programming languages

C
C#
C++
Java
Python

Go
Haskell
Java
JavaScript
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

C++
Java

Server-side scripts

Stored procedures

user defined functions

Triggers

yes, Notifications (with Streaming only)

yes

triggers when inserted values for one or more columns fall within a specified range

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency or Eventual Consistency depending on configuration

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, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

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, run db with in-memory only mode

yes

GPU vRAM or System RAM

yes

User concepts

Access control

yes (enterprise version only)

yes

Access rights for users and roles on table level

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

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