DBMS > AgensGraph vs. Google BigQuery vs. InfluxDB vs. Newts

System Properties Comparison AgensGraph vs. Google BigQuery vs. InfluxDB vs. Newts

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Large scale data warehouse service with append-only tables

DBMS for storing time series, events and metrics

Time Series DBMS based on Cassandra

Primary database model

Graph DBMS
Relational DBMS

Relational 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	0.18
Rank	#315	Overall
	#28	Graph DBMS
	#141	Relational DBMS

Score	50.58
Rank	#19	Overall
	#13	Relational DBMS

Score	21.47
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.00
Rank	#386	Overall
	#41	Time Series DBMS

Website

bitnine.net/agensgraph

cloud.google.com/bigquery

www.influxdata.com/products/influxdb-overview

opennms.github.io/newts

Technical documentation

bitnine.net/documentation

cloud.google.com/bigquery/docs

docs.influxdata.com/influxdb

github.com/OpenNMS/newts/wiki

Developer

Bitnine Global Inc.

Google

OpenNMS Group

Initial release

2016

2010

2013

2014

Current release

2.1, December 2018

2.7.6, April 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

MIT-License; commercial enterprise version available

Open Source

Apache 2.0

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

Java

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X

through Homebrew

Linux
OS X
Windows

Data scheme

depending on used data model

yes

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

Cypher Query Language
JDBC

RESTful HTTP/JSON API

HTTP API
JSON over UDP

HTTP REST
Java API

Supported programming languages

C
Java
JavaScript
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

Java

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

none

Sharding

in enterprise version only

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

in enterprise version only

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Depending on used storage engine

User concepts

Access control

fine grained access rights according to SQL-standard

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

Google Cloud Identity & Access Management (IAM)

simple rights management via user accounts

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