DBMS > BigObject vs. Blueflood vs. Hawkular Metrics vs. Snowflake

System Properties Comparison BigObject vs. Blueflood vs. Hawkular Metrics vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Scalable TimeSeries DBMS based on Cassandra

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Time Series DBMS

Relational DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

Technical documentation

docs.bigobject.io

github.com/rax-maas/blueflood/wiki

www.hawkular.org/hawkular-metrics/docs/user-guide

docs.snowflake.net/manuals/index.html

Developer

BigObject, Inc.

Rackspace

Community supported by Red Hat

Snowflake Computing Inc.

Initial release

2015

2013

2014

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

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

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
OS X

Linux
OS X
Windows

hosted

Data scheme

yes

predefined scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

HTTP REST

CLI Client
JDBC
ODBC

Supported programming languages

Go
Java
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

user defined functions

Triggers

yes

via Hawkular Alerting

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding

based on Cassandra

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

selectable replication factor

based on Cassandra

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

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