DBMS > Bangdb vs. Heroic vs. InfluxDB vs. LevelDB vs. Linter

System Properties Comparison Bangdb vs. Heroic vs. InfluxDB vs. LevelDB vs. Linter

Editorial information provided by DB-Engines

Name

Description

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

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

DBMS for storing time series, events and metrics

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

RDBMS for high security requirements

Primary database model

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

with GEO package

Spatial 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	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	22.12
Rank	#28	Overall
	#1	Time Series DBMS

Score	2.33
Rank	#111	Overall
	#19	Key-value stores

Score	0.03
Rank	#368	Overall
	#156	Relational DBMS

Website

bangdb.com

github.com/spotify/heroic

www.influxdata.com/products/influxdb-overview

github.com/google/leveldb

linter.ru

Technical documentation

docs.bangdb.com

spotify.github.io/heroic

docs.influxdata.com/influxdb

github.com/google/leveldb/blob/main/doc/index.md

Developer

Sachin Sinha, BangDB

Spotify

Google

relex.ru

Initial release

2012

2014

2013

2011

1990

Current release

BangDB 2.0, October 2021

2.7.6, April 2024

1.23, February 2021

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache 2.0

Open Source

MIT-License; commercial enterprise version available

Open Source

BSD

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++

Java

C++

C and C++

Server operating systems

Linux

Linux
OS X

through Homebrew

Illumos
Linux
OS X
Windows

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

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 and Strings

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

SQL-like query language

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

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

HTTP API
JSON over UDP

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

C
C#
C++
Java
Python

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes, Notifications (with Streaming only)

yes

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

in enterprise version only

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

selectable replication factor

in enterprise version only

none

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

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 automatic compression on writes

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

Depending on used storage engine

User concepts

Access control

yes (enterprise version only)

simple rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

InfluxData is the creator of InfluxDB , the open source time series database. It...
» more

Competitive advantages

Time to Value InfluxDB is available in all the popular languages and frameworks,...
» more

Typical application scenarios

IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more

Key customers

InfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more

Market metrics

Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more

Licensing and pricing models

Open source core with closed source clustering available either on-premise or on...
» more

News

Deploying InfluxDB and Telegraf to Monitor Kubernetes
17 September 2024

Telegraf 1.32 Release Notes
13 September 2024

An Introductory Guide to Cloud Security for IIoT
12 September 2024

Building Real-Time Android Apps with InfluxDB Cloud: Data Logging, Querying, and Visualization
10 September 2024

How to Use InfluxDB for Real-Time SpringBoot Application Monitoring
5 September 2024

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

Why Build a Time Series Data Platform?
20 July 2017, Paul Dix (guest author)

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

InfluxData's Latest Updates Optimize Time Series Data for Better Performance, Scale and Management
19 September 2024, Integration Developers

Run and manage open source InfluxDB databases with Amazon Timestream
14 March 2024, AWS Blog

InfluxData avoids ’AI magic beans’ in InfluxDB time series database update for enterprises
4 September 2024, VentureBeat

InfluxData Enhances InfluxDB 3.0 with Performance Upgrades and Self-Managed Option
5 September 2024, Datanami

InfluxData makes performance, storage improvements to InfluxDB 3.0
4 September 2024, InfoWorld

provided by Google News

Inside the "Fallguys" malware that steals your browsing data and gaming IMs; continued attack on open source software
2 September 2020, Sonatype Blog

Pliops unveils XDP-Rocks for RocksDB
19 October 2022, Blocks & Files

Threat Thursday: BlackGuard Infostealer Rises from Russian Underground Markets
21 April 2022, BlackBerry Blog

AMD EPYC vs. Intel Xeon Cascadelake With Facebook's RocksDB Database
17 October 2019, Phoronix

RocksDB - Facebook's Database Now Open Source
21 November 2013, iProgrammer

provided by Google News

Share this page