DBMS > Manticore Search vs. Microsoft Azure Cosmos DB vs. Newts vs. Quasardb vs. Splunk

System Properties Comparison Manticore Search vs. Microsoft Azure Cosmos DB vs. Newts vs. Quasardb vs. Splunk

Editorial information provided by DB-Engines

Name

Description

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

Globally distributed, horizontally scalable, multi-model database service

Time Series DBMS based on Cassandra

Distributed, high-performance timeseries database

Analytics Platform for Big Data

Primary database model

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Search engine

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Spatial DBMS

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

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

manticoresearch.com

azure.microsoft.com/services/cosmos-db

opennms.github.io/newts

quasar.ai

www.splunk.com

Technical documentation

manual.manticoresearch.com

learn.microsoft.com/azure/cosmos-db

github.com/OpenNMS/newts/wiki

doc.quasar.ai/master

docs.splunk.com/Documentation/Splunk

Developer

Manticore Software

Microsoft

OpenNMS Group

quasardb

Splunk Inc.

Initial release

2017

2014

2009

2003

Current release

6.0, February 2023

3.14.1, January 2024

License

Commercial or Open Source

Open Source

GPL version 2

commercial

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

commercial

Limited free edition and free developer edition available

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

C++

Java

C++

Server operating systems

FreeBSD
Linux
macOS
Windows

hosted

Linux
OS X
Windows

BSD
Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Data scheme

Fixed schema

schema-free

yes

Typing

predefined data types such as float or date

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

yes

JSON types

yes

integer and binary

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

yes

Secondary indexes

yes

full-text index on all search fields

yes

All properties auto-indexed by default

yes

with tags

yes

SQL

Support of SQL

SQL-like query language

Splunk Search Processing Language for search commands

APIs and other access methods

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

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP REST
Java API

HTTP API

HTTP REST

Supported programming languages

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Java

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

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

JavaScript

yes

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

Implicit feature of the cloud service

Sharding

based on Cassandra

Sharding

consistent hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication based on Galera library

yes

Implicit feature of the cloud service

selectable replication factor

based on Cassandra

Source-replica replication with selectable replication factor

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual 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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

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

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

Access rights can be defined down to the item level

Cryptographically strong user authentication and audit trail

Access rights for users and roles

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