DBMS > Bangdb vs. BigchainDB vs. Drizzle vs. Heroic vs. Kinetica

System Properties Comparison Bangdb vs. BigchainDB vs. Drizzle vs. Heroic vs. Kinetica

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

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

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

Primary database model

Document store
Graph DBMS
Time Series DBMS

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	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	0.42
Rank	#261	Overall
	#120	Relational DBMS

Website

bangdb.com

www.bigchaindb.com

github.com/spotify/heroic

www.kinetica.com

Technical documentation

docs.bangdb.com

bigchaindb.readthedocs.io/en/latest

spotify.github.io/heroic

docs.kinetica.com

Developer

Sachin Sinha, BangDB

Drizzle project, originally started by Brian Aker

Spotify

Kinetica

Initial release

2012

2016

2008

2014

2012

Current release

BangDB 2.0, October 2021

7.2.4, September 2012

7.1, August 2021

License

Commercial or Open Source

Open Source

BSD 3

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

C, C++

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: 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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

via Elasticsearch

yes

SQL

Support of SQL

SQL like support with command line tool

yes

with proprietary extensions

SQL-like DML and DDL statements

APIs and other access methods

Proprietary protocol
RESTful HTTP API

CLI Client
RESTful HTTP API

JDBC

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

JDBC
ODBC
RESTful HTTP API

Supported programming languages

C
C#
C++
Java
Python

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

yes, Notifications (with Streaming only)

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

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

Tunable consistency, set CAP knob accordingly

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, 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

User concepts

Access control

yes (enterprise version only)

yes

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users and roles on table level

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More resources

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