DBMS > Bangdb vs. Google BigQuery vs. InfluxDB vs. TerminusDB

System Properties Comparison Bangdb vs. Google BigQuery vs. InfluxDB vs. TerminusDB

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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

Large scale data warehouse service with append-only tables

DBMS for storing time series, events and metrics

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Graph DBMS

Secondary database models

Spatial DBMS

with GEO package

Document store
RDF store

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

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

bangdb.com

cloud.google.com/bigquery

www.influxdata.com/products/influxdb-overview

terminusdb.com

Technical documentation

docs.bangdb.com

cloud.google.com/bigquery/docs

docs.influxdata.com/influxdb

terminusdb.github.io/terminusdb/#

Developer

Sachin Sinha, BangDB

Google

DataChemist Ltd.

Initial release

2012

2010

2013

2018

Current release

BangDB 2.0, October 2021

2.7.6, April 2024

11.0.0, January 2023

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

MIT-License; commercial enterprise version available

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++

Prolog, Rust

Server operating systems

Linux

hosted

Linux
OS X

through Homebrew

Linux

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

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

SQL

Support of SQL

SQL like support with command line tool

yes

SQL-like query language

SQL-like query language (WOQL)

APIs and other access methods

Proprietary protocol
RESTful HTTP API

RESTful HTTP/JSON API

HTTP API
JSON over UDP

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C
C#
C++
Java
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

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

none

Sharding

in enterprise version only

Graph 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

Journaling Streams

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying 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

in-memory journaling

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)

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

simple rights management via user accounts

Role-based access control

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