DBMS > Bangdb vs. CockroachDB vs. Graphite vs. Ignite

System Properties Comparison Bangdb vs. CockroachDB vs. Graphite vs. Ignite

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Key-value store
Relational DBMS

Secondary database models

Spatial DBMS

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

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

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Website

bangdb.com

www.cockroachlabs.com

github.com/graphite-project/graphite-web

ignite.apache.org

Technical documentation

docs.bangdb.com

www.cockroachlabs.com/docs

graphite.readthedocs.io

apacheignite.readme.io/docs

Developer

Sachin Sinha, BangDB

Cockroach Labs

Chris Davis

Apache Software Foundation

Initial release

2012

2015

2006

2015

Current release

BangDB 2.0, October 2021

23.1.1, May 2023

Apache Ignite 2.6

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache 2.0, commercial license available

Open Source

Apache 2.0

Open Source

Apache 2.0

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, .Net

Server operating systems

Linux

Linux
macOS
Windows

Linux
Unix

Linux
OS X
Solaris
Windows

Data scheme

schema-free

dynamic schema

yes

Typing

predefined data types such as float or date

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

yes

Numeric data only

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

yes, wire compatible with PostgreSQL

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC

HTTP API
Sockets

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Supported programming languages

C
C#
C++
Java
Python

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

JavaScript (Node.js)
Python

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

Triggers

yes, Notifications (with Streaming only)

yes (cache interceptors and events)

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

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication using RAFT

none

yes (replicated cache)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

none

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

locking

yes

Durability

Support for making data persistent

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

yes (enterprise version only)

Role-based access control

Security Hooks for custom implementations

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

show all

Recent citations in the news

CockroachDB 23.2 Enhances Enterprise Architectures with Improved Postgres Compatibility and Built-in Resilience
18 January 2024, PR Newswire

CockroachDB tempts legacy databases to crawl into the cloud age
29 January 2024, The Register

How to Unlock Real-Time Data Streams with CockroachDB and Amazon MSK | Amazon Web Services
6 November 2023, AWS Blog

How DoorDash Migrated from Aurora Postgres to CockroachDB
5 December 2023, The New Stack

CockroachDB's Latest Enhancements Focus on Resilience
18 January 2024, Database Trends and Applications

provided by Google News

Grafana Labs Announces Mimir Time Series Database
1 April 2022, Datanami

The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data
10 December 2018, Uber

Getting Started with Monitoring using Graphite
23 January 2015, InfoQ.com

The value of time series data and TSDBs
10 June 2021, InfoWorld

Getting Started with Infrastructure Monitoring
11 September 2023, The New Stack

provided by Google News

Share this page