DBMS > BigObject vs. Blueflood vs. HBase vs. Percona Server for MySQL vs. Snowflake

System Properties Comparison BigObject vs. Blueflood vs. HBase vs. Percona Server for MySQL vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Scalable TimeSeries DBMS based on Cassandra

Wide-column store based on Apache Hadoop and on concepts of BigTable

Enhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.

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

Wide column store

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	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	2.03
Rank	#122	Overall
	#57	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

bigobject.io

blueflood.io

hbase.apache.org

www.percona.com/software/mysql-database/percona-server

www.snowflake.com

Technical documentation

docs.bigobject.io

github.com/rax-maas/blueflood/wiki

hbase.apache.org/book.html

www.percona.com/downloads/Percona-Server-LATEST

docs.snowflake.net/manuals/index.html

Developer

BigObject, Inc.

Rackspace

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Percona

Snowflake Computing Inc.

Initial release

2015

2013

2008

2014

Current release

2.3.4, January 2021

8.0.36-28, 2024

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

Open Source

Apache version 2

Open Source

GPL version 2

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

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
Unix
Windows

using Cygwin

Linux

hosted

Data scheme

yes

predefined scheme

schema-free, schema definition possible

yes

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

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

Java API
RESTful HTTP API
Thrift

ADO.NET
JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

yes

Coprocessors in Java

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

Multi-source replication
Source-replica replication
XtraDB Cluster

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency or Eventual Consistency

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

Single row ACID (across millions of columns)

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

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Users with fine-grained authorization concept

no user groups or roles

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

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