DBMS > Datomic vs. Drizzle vs. Google Cloud Firestore vs. Snowflake vs. TerarkDB

System Properties Comparison Datomic vs. Drizzle vs. Google Cloud Firestore vs. Snowflake vs. TerarkDB

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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.

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

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

www.datomic.com

firebase.google.com/products/firestore

www.snowflake.com

github.com/bytedance/terarkdb

Technical documentation

docs.datomic.com

firebase.google.com/docs/firestore

docs.snowflake.net/manuals/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Cognitect

Drizzle project, originally started by Brian Aker

Google

Snowflake Computing Inc.

ByteDance, originally Terark

Initial release

2012

2008

2017

2014

2016

Current release

1.0.7075, December 2023

7.2.4, September 2012

License

Commercial or Open Source

commercial

limited edition free

Open Source

GNU GPL

commercial

restricted open source version 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

Java, Clojure

C++

Server operating systems

All OS with a Java VM

FreeBSD
Linux
OS X

hosted

Data scheme

yes

schema-free

yes

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

schema-free

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

yes

with proprietary extensions

yes

APIs and other access methods

RESTful HTTP API

JDBC

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

CLI Client
JDBC
ODBC

C++ API
Java API

Supported programming languages

Clojure
Java

C
C++
Java
PHP

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

JavaScript (Node.js)
Python

C++
Java

Server-side scripts

Stored procedures

yes

Transaction Functions

yes, Firebase Rules & Cloud Functions

user defined functions

Triggers

By using transaction functions

hooks for callbacks inside the server can be used.

yes, with Cloud Functions

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Multi-source replication
Source-replica replication

Multi-source replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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

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

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