DBMS > Bangdb vs. InfluxDB vs. Lovefield vs. Riak TS vs. Sadas Engine

System Properties Comparison Bangdb vs. InfluxDB vs. Lovefield vs. Riak TS vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

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

DBMS for storing time series, events and metrics

Embeddable relational database for web apps written in pure JavaScript

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Document store
Graph DBMS
Time Series DBMS

Secondary database models

Spatial DBMS

with GEO package

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	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

bangdb.com

www.influxdata.com/products/influxdb-overview

google.github.io/lovefield

www.sadasengine.com

Technical documentation

docs.bangdb.com

docs.influxdata.com/influxdb

github.com/google/lovefield/blob/master/docs/spec_index.md

www.tiot.jp/riak-docs/riak/ts/latest

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Sachin Sinha, BangDB

Google

Open Source, formerly Basho Technologies

SADAS s.r.l.

Initial release

2012

2013

2014

2015

2006

Current release

BangDB 2.0, October 2021

2.7.6, April 2024

2.1.12, February 2017

3.0.0, September 2022

8.0

License

Commercial or Open Source

Open Source

BSD 3

Open Source

MIT-License; commercial enterprise version available

Open Source

Apache 2.0

Open Source

commercial

free trial version available

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++

JavaScript

Erlang

C++

Server operating systems

Linux

Linux
OS X

through Homebrew

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
OS X

AIX
Linux
Windows

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

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

restricted

yes

SQL

Support of SQL

SQL like support with command line tool

SQL-like query language

via JavaScript builder pattern

yes, limited

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

HTTP API
JSON over UDP

HTTP API
Native Erlang Interface

JDBC
ODBC
Proprietary protocol

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

JavaScript

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

Erlang

Triggers

yes, Notifications (with Streaming only)

Using read-only observers

yes

pre-commit hooks and post-commit hooks

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

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

in enterprise version only

none

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

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

yes

using MemoryDB

yes

managed by 'Learn by Usage'

User concepts

Access control

yes (enterprise version only)

simple rights management via user accounts

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Key customers

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Market metrics

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Licensing and pricing models

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More resources

DB-Engines blog posts

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