DBMS > EsgynDB vs. Google BigQuery vs. Netezza vs. OpenTSDB

System Properties Comparison EsgynDB vs. Google BigQuery vs. Netezza vs. OpenTSDB

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Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Large scale data warehouse service with append-only tables

Data warehouse and analytics appliance part of IBM PureSystems

Scalable Time Series DBMS based on HBase

Primary database model

Relational DBMS

Time Series DBMS

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Website

www.esgyn.cn

cloud.google.com/bigquery

www.ibm.com/products/netezza

opentsdb.net

Technical documentation

cloud.google.com/bigquery/docs

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

Developer

Esgyn

Google

IBM

currently maintained by Yahoo and other contributors

Initial release

2015

2010

2000

2011

License

Commercial or Open Source

commercial

Open Source

LGPL

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++, Java

Java

Server operating systems

Linux

hosted

Linux

included in appliance

Linux
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

APIs and other access methods

ADO.NET
JDBC
ODBC

RESTful HTTP/JSON API

JDBC
ODBC
OLE DB

HTTP API
Telnet API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++
Fortran
Java
Lua
Perl
Python
R

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

in JavaScript

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

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

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.

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)

Users with fine-grained authorization concept

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