DBMS > Microsoft Azure Cosmos DB vs. Microsoft Azure Synapse Analytics vs. Qdrant vs. Sphinx vs. WakandaDB

System Properties Comparison Microsoft Azure Cosmos DB vs. Microsoft Azure Synapse Analytics vs. Qdrant vs. Sphinx vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

Globally distributed, horizontally scalable, multi-model database service

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

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

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

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

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

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/services/synapse-analytics

github.com/qdrant/qdrant
qdrant.tech

sphinxsearch.com

wakanda.github.io

Technical documentation

learn.microsoft.com/azure/cosmos-db

docs.microsoft.com/azure/synapse-analytics

qdrant.tech/documentation

sphinxsearch.com/docs

wakanda.github.io/doc

Developer

Microsoft

Qdrant

Sphinx Technologies Inc.

Wakanda SAS

Initial release

2014

2016

2021

2001

2012

Current release

3.5.1, February 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GPL version 2, commercial licence available

Open Source

AGPLv3, extended commercial license 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++

C++, JavaScript

Server operating systems

hosted

Docker
Linux
macOS
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

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.

Secondary indexes

yes

All properties auto-indexed by default

yes

Keywords, numberic ranges, geo, full-text

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language (SphinxQL)

APIs and other access methods

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

ADO.NET
JDBC
ODBC

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Proprietary protocol

RESTful HTTP API

Supported programming languages

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

C#
Java
PHP

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

JavaScript

Server-side scripts

Stored procedures

JavaScript

Transact SQL

yes

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Collection-level replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

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

Immediate Consistency

Eventual Consistency, tunable consistency

Immediate Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

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 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

yes

Key-based authentication

yes

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