DBMS > Blueflood vs. Google BigQuery vs. Newts vs. OpenTSDB vs. Quasardb

System Properties Comparison Blueflood vs. Google BigQuery vs. Newts vs. OpenTSDB vs. Quasardb

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

Large scale data warehouse service with append-only tables

Time Series DBMS based on Cassandra

Scalable Time Series DBMS based on HBase

Distributed, high-performance timeseries database

Primary database model

Time Series DBMS

Relational DBMS

Time Series DBMS

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Website

blueflood.io

cloud.google.com/bigquery

opennms.github.io/newts

opentsdb.net

quasar.ai

Technical documentation

github.com/rax-maas/blueflood/wiki

cloud.google.com/bigquery/docs

github.com/OpenNMS/newts/wiki

opentsdb.net/docs/build/html/index.html

doc.quasar.ai/master

Developer

Rackspace

Google

OpenNMS Group

currently maintained by Yahoo and other contributors

quasardb

Initial release

2013

2010

2014

2011

2009

Current release

3.14.1, January 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

Open Source

LGPL

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

C++

Server operating systems

Linux
OS X

hosted

Linux
OS X
Windows

Linux
Windows

BSD
Linux
OS X
Windows

Data scheme

predefined scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

yes

integer and binary

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

with tags

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

HTTP REST

RESTful HTTP/JSON API

HTTP REST
Java API

HTTP API
Telnet API

HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java

Erlang
Go
Java
Python
R
Ruby

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

based on Cassandra

Sharding

based on HBase

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

selectable replication factor

based on Cassandra

selectable replication factor

based on HBase

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

based on HBase

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

Cryptographically strong user authentication and audit trail

More information provided by the system vendor

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.