DBMS > atoti vs. Bangdb vs. Dgraph vs. Graphite

System Properties Comparison atoti vs. Bangdb vs. Dgraph vs. Graphite

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

Distributed and scalable native Graph DBMS

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Primary database model

Object oriented DBMS

Document store
Graph DBMS
Time Series DBMS

Graph DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.61
Rank	#243	Overall
	#11	Object oriented DBMS

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Website

atoti.io

bangdb.com

dgraph.io

github.com/graphite-project/graphite-web

Technical documentation

docs.atoti.io

docs.bangdb.com

dgraph.io/docs

graphite.readthedocs.io

Developer

ActiveViam

Sachin Sinha, BangDB

Dgraph Labs, Inc.

Chris Davis

Initial release

2012

2016

2006

Current release

BangDB 2.0, October 2021

License

Commercial or Open Source

commercial

free versions available

Open Source

BSD 3

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

Java

C, C++

Python

Server operating systems

Linux

Linux
OS X
Windows

Linux
Unix

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

yes

Numeric data only

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

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL like support with command line tool

APIs and other access methods

Proprietary protocol
RESTful HTTP API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

HTTP API
Sockets

Supported programming languages

C
C#
C++
Java
Python

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Python

Triggers

yes, Notifications (with Streaming only)

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

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

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Synchronous replication via Raft

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

none

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes, optimistic concurrency control

yes

locking

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

yes, run db with in-memory only mode

User concepts

Access control

yes (enterprise version only)

Planned for future releases

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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

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Recent citations in the news

Overview Of Atoti: A Python BI Analytics Tool – AIM
14 May 2021, Analytics India Magazine

FRTB product of the year: ActiveViam
28 November 2023, Risk.net

provided by Google News

Dgraph on AWS: Setting up a horizontally scalable graph database
1 September 2020, AWS Blog

Dgraph Rises to the Top Graph Database on GitHub With 11 G2 Badges and 11M Downloads
26 May 2021, Business Wire

Dgraph raises $11.5 million for scalable graph database solutions
31 July 2019, VentureBeat

Dgraph raises $3M for its open-source distributed graph database, hits 1.0 release
19 December 2017, TechCrunch

provided by Google News

Try out the Graphite monitoring tool for time-series data
29 October 2019, TechTarget

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

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

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

Real-Time Performance and Health Monitoring Using Netdata
2 September 2019, CNX Software

provided by Google News

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