DBMS > LMDB vs. Microsoft Azure Cosmos DB vs. Qdrant vs. ScyllaDB

System Properties Comparison LMDB vs. Microsoft Azure Cosmos DB vs. Qdrant vs. ScyllaDB

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Editorial information provided by DB-Engines

Name

Description

A high performant, light-weight, embedded key-value database library

Globally distributed, horizontally scalable, multi-model database service

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

Cassandra and DynamoDB compatible wide column store

Primary database model

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Vector DBMS

Wide column store

Secondary database models

Spatial DBMS

Key-value store

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

Score	2.09
Rank	#121	Overall
	#20	Key-value stores

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.28
Rank	#167	Overall
	#6	Vector DBMS

Score	4.08
Rank	#76	Overall
	#5	Wide column stores

Website

www.symas.com/symas-embedded-database-lmdb

azure.microsoft.com/services/cosmos-db

github.com/qdrant/qdrant
qdrant.tech

www.scylladb.com

Technical documentation

www.lmdb.tech/doc

learn.microsoft.com/azure/cosmos-db

qdrant.tech/documentation

docs.scylladb.com

Developer

Symas

Microsoft

Qdrant

ScyllaDB

Initial release

2011

2014

2021

2015

Current release

0.9.32, January 2024

ScyllaDB Open Source 5.4.1, January 2024

License

Commercial or Open Source

Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Open Source (AGPL), commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Rust

C++

Server operating systems

Linux
Unix
Windows

hosted

Docker
Linux
macOS
Windows

Linux

Data scheme

schema-free

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

All properties auto-indexed by default

yes

Keywords, numberic ranges, geo, full-text

yes

cluster global secondary indices

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements (CQL)

APIs and other access methods

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 (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

Supported programming languages

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

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

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

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

Server-side scripts

Stored procedures

JavaScript

yes, Lua

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

Collection-level replication

selectable replication factor

Representation of geographical distribution of servers is possible

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

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency, tunable consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Atomicity and isolation are supported for single operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

in-memory tables

User concepts

Access control

Access rights can be defined down to the item level

Key-based authentication

Access rights for users can be defined per object

More information provided by the system vendor

Specific characteristics

ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
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Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenarios

ScyllaDB is ideal for applications that require high throughput and low latency at...
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Key customers

Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
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Market metrics

ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
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Licensing and pricing models

ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
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