DBMS > Apache HBase vs. NSDb vs. Postgres-XL

System Properties Comparison Apache HBase vs. NSDb vs. Postgres-XL

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Editorial information provided by DB-Engines

Name

Description

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Wide column store

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	25.00
Rank	#26	Overall
	#2	Wide column stores

Score	0.00
Rank	#392	Overall
	#44	Time Series DBMS

Score	0.41
Rank	#261	Overall
	#121	Relational DBMS

Website

hbase.apache.org

nsdb.io

www.postgres-xl.org

Technical documentation

hbase.apache.org/book.html

nsdb.io/Architecture

www.postgres-xl.org/documentation

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Initial release

2008

2017

2014

since 2012, originally named StormDB

Current release

2.3.4, January 2021

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache Version 2.0

Open Source

Mozilla public license

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Java, Scala

Server operating systems

Linux
Unix
Windows

using Cygwin

Linux
macOS

Data scheme

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

options to bring your own types, AVRO

yes: int, bigint, decimal, string

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

XML type, but no XML query functionality

Secondary indexes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

distributed, parallel query execution

APIs and other access methods

Java API
RESTful HTTP API
Thrift

gRPC
HTTP REST
WebSocket

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

Java
Scala

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

Coprocessors in Java

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Single row ACID (across millions of columns)

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Apache HBase online migration to Amazon EMR
23 October 2024, AWS Blog

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5 June 2014, Facebook Engineering

Set up a standalone HBase local instance and connect to it with Python Happybase
9 February 2020, Towards Data Science

Horizontal Scalability with HBase
26 November 2013, Ericsson

How to interact with HBase using HBase shell [Tutorial]
25 June 2018, packtpub.com

provided by Google News

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