DBMS > Apache HBase vs. Apache Solr vs. NSDb

System Properties Comparison Apache HBase vs. Apache Solr vs. NSDb

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Editorial information provided by DB-Engines

Name

Description

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

A widely used distributed, scalable search engine based on Apache Lucene

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

Primary database model

Wide column store

Search engine

Time Series DBMS

Secondary database models

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	32.47
Rank	#24	Overall
	#3	Search engines

Score	0.00
Rank	#392	Overall
	#44	Time Series DBMS

Website

hbase.apache.org

solr.apache.org

nsdb.io

Technical documentation

hbase.apache.org/book.html

solr.apache.org/resources.html

nsdb.io/Architecture

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Apache Software Foundation

Initial release

2008

2006

2017

Current release

2.3.4, January 2021

9.6.1, May 2024

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache Version 2

Open Source

Apache Version 2.0

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

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux
macOS

Data scheme

schema-free, schema definition possible

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

options to bring your own types, AVRO

yes

supports customizable data types and automatic typing

yes: int, bigint, decimal, string

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

All search fields are automatically indexed

all fields are automatically indexed

SQL

Support of SQL

Solr Parallel SQL Interface

SQL-like query language

APIs and other access methods

Java API
RESTful HTTP API
Thrift

Java API
RESTful HTTP/JSON API

gRPC
HTTP REST
WebSocket

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Java
Scala

Server-side scripts

Stored procedures

yes

Coprocessors in Java

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Single row ACID (across millions of columns)

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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

yes

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More resources

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