DBMS > BigchainDB vs. Drizzle vs. Heroic vs. Kinetica vs. Transwarp ArgoDB

System Properties Comparison BigchainDB vs. Drizzle vs. Heroic vs. Kinetica vs. Transwarp ArgoDB

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Fully vectorized database across both GPUs and CPUs

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

Search engine

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

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	0.12
Rank	#348	Overall
	#151	Relational DBMS

Website

www.bigchaindb.com

github.com/spotify/heroic

www.kinetica.com

www.transwarp.cn/en/product/argodb

Technical documentation

bigchaindb.readthedocs.io/en/latest

spotify.github.io/heroic

docs.kinetica.com

docs.transwarp.cn/#/documents-support/docs?category=ARGODB

Developer

Drizzle project, originally started by Brian Aker

Spotify

Kinetica

Transwarp

Initial release

2016

2008

2014

2012

Current release

7.2.4, September 2012

7.1, August 2021

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

GNU GPL

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Python

C++

Java

C, C++

Server operating systems

Linux

FreeBSD
Linux
OS X

Linux

Data scheme

schema-free

yes

schema-free

yes

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.

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like DML and DDL statements

yes

APIs and other access methods

CLI Client
RESTful HTTP API

JDBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
ODBC
RESTful HTTP API

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

C
C++
Java
PHP

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

hooks for callbacks inside the server can be used.

yes

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
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

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

GPU vRAM or System RAM

User concepts

Access control

yes

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users and roles on table level

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

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