DBMS > Manticore Search vs. Microsoft Azure Cosmos DB vs. Qdrant vs. Sphinx vs. Splunk

System Properties Comparison Manticore Search vs. Microsoft Azure Cosmos DB vs. Qdrant vs. Sphinx 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

A high-performance vector database with neural network or semantic-based matching

Open source search engine for searching in data from different sources, e.g. relational databases

Analytics Platform for Big Data

Primary database model

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Vector 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	1.16
Rank	#175	Overall
	#6	Vector DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

manticoresearch.com

azure.microsoft.com/services/cosmos-db

github.com/qdrant/qdrant
qdrant.tech

sphinxsearch.com

www.splunk.com

Technical documentation

manual.manticoresearch.com

learn.microsoft.com/azure/cosmos-db

qdrant.tech/documentation

sphinxsearch.com/docs

docs.splunk.com/Documentation/Splunk

Developer

Manticore Software

Microsoft

Qdrant

Sphinx Technologies Inc.

Splunk Inc.

Initial release

2017

2014

2021

2001

2003

Current release

6.0, February 2023

3.5.1, February 2023

License

Commercial or Open Source

Open Source

GPL version 2

commercial

Open Source

Apache Version 2.0

Open Source

GPL version 2, commercial licence available

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++

Rust

C++

Server operating systems

FreeBSD
Linux
macOS
Windows

hosted

Docker
Linux
macOS
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
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

Numbers, Strings, Geo, 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

yes

Secondary indexes

yes

full-text index on all search fields

yes

All properties auto-indexed by default

yes

Keywords, numberic ranges, geo, full-text

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

SQL-like query language (SphinxQL)

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

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Proprietary protocol

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

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

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

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication based on Galera library

yes

Implicit feature of the cloud service

Collection-level replication

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

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, tunable 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

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

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

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 rights can be defined down to the item level

Key-based authentication

Access rights for users and roles

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