DBMS > Apache Kylin vs. etcd vs. HBase vs. Solr vs. SQLite

System Properties Comparison Apache Kylin vs. etcd vs. HBase vs. Solr vs. SQLite

Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

A distributed reliable key-value store

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

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

Widely used embeddable, in-process RDBMS

Primary database model

Secondary database models

Spatial DBMS

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

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	41.02
Rank	#24	Overall
	#3	Search engines

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

kylin.apache.org

etcd.io
github.com/etcd-io/etcd

hbase.apache.org

solr.apache.org

www.sqlite.org

Technical documentation

kylin.apache.org/docs

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

hbase.apache.org/book.html

solr.apache.org/resources.html

www.sqlite.org/docs.html

Developer

Apache Software Foundation, originally contributed from eBay Inc

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Apache Software Foundation

Dwayne Richard Hipp

Initial release

2015

2008

2006

2000

Current release

3.1.0, July 2020

3.4, August 2019

2.3.4, January 2021

9.6.1, May 2024

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

Apache version 2

Open Source

Apache Version 2

Open Source

Public Domain

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

Java

Server operating systems

Linux

FreeBSD
Linux
Windows

experimental

Linux
Unix
Windows

using Cygwin

All OS with a Java VM

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

server-less

Data scheme

yes

schema-free

schema-free, schema definition possible

yes

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

yes

dynamic column types

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

yes

supports customizable data types and automatic typing

yes

not rigid because of 'dynamic typing' concept.

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

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

Solr Parallel SQL Interface

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

gRPC
JSON over HTTP

Java API
RESTful HTTP API
Thrift

Java API
RESTful HTTP/JSON API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

Coprocessors in Java

Java plugins

Triggers

yes, watching key changes

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Multi-source replication
Source-replica replication

yes

none

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

Immediate Consistency or Eventual Consistency

Eventual 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)

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

yes

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.