DBMS > Apache Impala vs. Elasticsearch vs. Hawkular Metrics vs. Manticore Search vs. SQLite

System Properties Comparison Apache Impala vs. Elasticsearch vs. Hawkular Metrics vs. Manticore Search vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Multi-storage database for search, including full-text search.

Widely used embeddable, in-process RDBMS

Primary database model

Secondary database models

Document store

Document store
Spatial DBMS
Vector DBMS

Time Series DBMS

using the Manticore Columnar Library

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

impala.apache.org

www.elastic.co/elasticsearch

www.hawkular.org

manticoresearch.com

www.sqlite.org

Technical documentation

impala.apache.org/impala-docs.html

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

www.hawkular.org/hawkular-metrics/docs/user-guide

manual.manticoresearch.com

www.sqlite.org/docs.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Elastic

Community supported by Red Hat

Manticore Software

Dwayne Richard Hipp

Initial release

2013

2010

2014

2017

2000

Current release

4.1.0, June 2022

8.6, January 2023

6.0, February 2023

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Elastic License

Open Source

Apache 2.0

Open Source

GPL 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

C++

Java

C++

Server operating systems

Linux

All OS with a Java VM

Linux
OS X
Windows

FreeBSD
Linux
macOS
Windows

server-less

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free

Fixed schema

yes

dynamic column types

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

yes

All search fields are automatically indexed

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP/JSON API

HTTP REST

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

All languages supporting JDBC/ODBC

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

Go
Java
Python
Ruby

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

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

user defined functions and integration of map-reduce

yes

user defined functions

Triggers

yes

by using the 'percolation' feature

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Partitioning is done manually, search queries against distributed index is supported

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

selectable replication factor

based on Cassandra

Synchronous replication based on Galera library

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Memcached and Redis integration

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

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