DBMS > EsgynDB vs. Hypertable vs. Netezza vs. QuestDB

System Properties Comparison EsgynDB vs. Hypertable vs. Netezza vs. QuestDB

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

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

An open source BigTable implementation based on distributed file systems such as Hadoop

Data warehouse and analytics appliance part of IBM PureSystems

A high performance open source SQL database for time series data

Primary database model

Secondary database models

Relational DBMS

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

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	7.56
Rank	#48	Overall
	#31	Relational DBMS

Score	2.81
Rank	#98	Overall
	#7	Time Series DBMS

Website

www.esgyn.cn

www.ibm.com/products/netezza

questdb.io

Technical documentation

questdb.io/docs

Developer

Esgyn

Hypertable Inc.

IBM

QuestDB Technology Inc

Initial release

2015

2009

2000

2014

Current release

0.9.8.11, March 2016

License

Commercial or Open Source

commercial

Open Source

GNU version 3. Commercial license available

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, Java

C++

Java (Zero-GC), C++, Rust

Server operating systems

Linux

Linux
OS X
Windows

an inofficial Windows port is available

Linux

included in appliance

Linux
macOS
Windows

Data scheme

yes

schema-free

yes

schema-free via InfluxDB Line Protocol

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.

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

SQL with time-series extensions

APIs and other access methods

ADO.NET
JDBC
ODBC

C++ API
Thrift

JDBC
ODBC
OLE DB

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C++
Java
Perl
PHP
Python
Ruby

C
C++
Fortran
Java
Lua
Perl
Python
R

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by timestamps)

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

selectable replication factor on file system level

Source-replica replication

Source-replica replication with eventual consistency

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID for single-table writes

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

through memory mapped files

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

More information provided by the system vendor

News

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13 August 2024

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