DBMS > Google Cloud Firestore vs. LMDB vs. OrientDB vs. Snowflake vs. Typesense

System Properties Comparison Google Cloud Firestore vs. LMDB vs. OrientDB vs. Snowflake vs. Typesense

Editorial information provided by DB-Engines

Name

Description

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

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

Multi-model DBMS (Document, Graph, Key/Value)

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

A typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

Primary database model

Document store

Key-value store

Document store
Graph DBMS
Key-value store

Relational DBMS

Search engine

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

Score	7.85
Rank	#51	Overall
	#8	Document stores

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

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.79
Rank	#210	Overall
	#14	Search engines

Website

firebase.google.com/products/firestore

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

orientdb.org

www.snowflake.com

typesense.org

Technical documentation

firebase.google.com/docs/firestore

www.lmdb.tech/doc

www.orientdb.com/docs/last/index.html

docs.snowflake.net/manuals/index.html

typesense.org/docs

Developer

Google

Symas

OrientDB LTD; CallidusCloud; SAP

Snowflake Computing Inc.

Initial release

2017

2011

2010

2014

2015

Current release

0.9.32, January 2024

3.2.29, March 2024

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

Open Source

GPL V3

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

Java

C++

Server operating systems

hosted

Linux
Unix
Windows

All OS with a Java JDK (>= JDK 6)

hosted

Linux

Data scheme

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

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

schema-free

pre-defined schema optional

Typing

predefined data types such as float or date

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

yes

SQL

Support of SQL

SQL-like query language, no joins

yes

APIs and other access methods

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

CLI Client
JDBC
ODBC

RESTful HTTP API

Supported programming languages

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

.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
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

Java, Javascript

user defined functions

Triggers

yes, with Cloud Functions

Hooks

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

Multi-source replication

yes

Multi-source replication using RAFT

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

yes

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Access rights for users and roles; record level security configurable

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

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