DBMS > LMDB vs. Pinecone vs. Snowflake

System Properties Comparison LMDB vs. Pinecone vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

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

A managed, cloud-native vector database

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Key-value store

Vector DBMS

Relational DBMS

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

Score	1.99
Rank	#125	Overall
	#21	Key-value stores

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

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

www.pinecone.io

www.snowflake.com

Technical documentation

www.lmdb.tech/doc

docs.pinecone.io/docs/overview

docs.snowflake.net/manuals/index.html

Developer

Symas

Pinecone Systems, Inc

Snowflake Computing Inc.

Initial release

2011

2019

2014

Current release

0.9.32, January 2024

License

Commercial or Open Source

Open Source

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

Server operating systems

Linux
Unix
Windows

hosted

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

String, Number, 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.

yes

Secondary indexes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

CLI Client
JDBC
ODBC

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

Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

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