DBMS > Bangdb vs. Graphite vs. IBM Db2 Event Store

System Properties Comparison Bangdb vs. Graphite vs. IBM Db2 Event Store

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Editorial information provided by DB-Engines

Name

Description

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

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Distributed Event Store optimized for Internet of Things use cases

Primary database model

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Event Store
Time Series 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	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Website

bangdb.com

github.com/graphite-project/graphite-web

www.ibm.com/products/db2-event-store

Technical documentation

docs.bangdb.com

graphite.readthedocs.io

www.ibm.com/docs/en/db2-event-store

Developer

Sachin Sinha, BangDB

Chris Davis

IBM

Initial release

2012

2006

2017

Current release

BangDB 2.0, October 2021

2.0

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache 2.0

commercial

free developer edition available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Python

C and C++

Server operating systems

Linux

Linux
Unix

Linux

Linux, macOS, Windows for the developer addition

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

SQL

Support of SQL

SQL like support with command line tool

yes

through the embedded Spark runtime

APIs and other access methods

Proprietary protocol
RESTful HTTP API

HTTP API
Sockets

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Supported programming languages

C
C#
C++
Java
Python

JavaScript (Node.js)
Python

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

Server-side scripts

Stored procedures

yes

Triggers

yes, Notifications (with Streaming only)

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Active-active shard 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

none

Eventual Consistency

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, optimistic concurrency control

yes

locking

No - written data is immutable

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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)

fine grained access rights according to SQL-standard

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More resources

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