DBMS > Elasticsearch vs. Manticore Search vs. Transwarp Hippo

System Properties Comparison Elasticsearch vs. Manticore Search vs. Transwarp Hippo

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Editorial information provided by DB-Engines

Name

Description

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

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

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Search engine

Vector DBMS

Secondary database models

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	135.35
Rank	#7	Overall
	#1	Search engines

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	0.00
Rank	#383	Overall
	#13	Vector DBMS

Website

www.elastic.co/elasticsearch

manticoresearch.com

www.transwarp.cn/en/subproduct/hippo

Technical documentation

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

manual.manticoresearch.com

Developer

Elastic

Manticore Software

Initial release

2010

2017

2023

Current release

8.6, January 2023

6.0, February 2023

1.0, May 2023

License

Commercial or Open Source

Open Source

Elastic License

Open Source

GPL version 2

commercial

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

C++

Server operating systems

All OS with a Java VM

FreeBSD
Linux
macOS
Windows

Linux
macOS

Data scheme

schema-free

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

Fixed schema

Typing

predefined data types such as float or date

yes

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

Vector, Numeric and 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.

Can index from XML

Secondary indexes

yes

All search fields are automatically indexed

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

APIs and other access methods

Java API
RESTful HTTP/JSON API

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

RESTful HTTP API

Supported programming languages

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

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

C++
Java
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication based on Galera library

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Immediate Consistency

Foreign keys

Referential integrity

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

Concurrency

Support for concurrent manipulation of data

yes

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

Role based access control and fine grained access rights

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More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2017
2 January 2018, Paul Andlinger, Matthias Gelbmann

Elasticsearch moved into the top 10 most popular database management systems
3 July 2017, Matthias Gelbmann

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

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Recent citations in the news

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