DBMS > Amazon Redshift vs. Elasticsearch vs. Manticore Search vs. NuoDB vs. TigerGraph

System Properties Comparison Amazon Redshift vs. Elasticsearch vs. Manticore Search vs. NuoDB vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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.

NuoDB is a webscale distributed database that supports SQL and ACID transactions

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

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	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

aws.amazon.com/redshift

www.elastic.co/elasticsearch

manticoresearch.com

www.3ds.com/nuodb-distributed-sql-database

www.tigergraph.com

Technical documentation

docs.aws.amazon.com/redshift

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

manual.manticoresearch.com

doc.nuodb.com

docs.tigergraph.com

Developer

Amazon (based on PostgreSQL)

Elastic

Manticore Software

Dassault Systèmes

originally NuoDB, Inc.

Initial release

2012

2010

2017

2013

2017

Current release

8.6, January 2023

6.0, February 2023

License

Commercial or Open Source

commercial

Open Source

Elastic License

Open Source

GPL version 2

commercial

limited edition free

commercial

Cloud-based only

Only available as a cloud service

yes

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

hosted

All OS with a Java VM

FreeBSD
Linux
macOS
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

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

Fixed schema

yes

Typing

predefined data types such as float or date

yes

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

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.

Can index from XML

Secondary indexes

restricted

yes

All search fields are automatically indexed

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

yes

SQL-like query language (GSQL)

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP/JSON API

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

ADO.NET
JDBC
ODBC

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

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

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

.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby

C++
Java

Server-side scripts

Stored procedures

user defined functions

in Python

yes

user defined functions

Java, SQL

yes

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

data is dynamically stored/cached on the nodes where it is read/written

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication based on Galera library

yes

Managed transparently by NuoDB

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

yes

informational only, not enforced by the system

yes

Relationships in graphs

Transaction concepts

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

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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.

yes

Memcached and Redis integration

yes

Temporary table

User concepts

Access control

fine grained access rights according to SQL-standard

Standard SQL roles/ privileges, Administrative Users

Role-based access control

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