DBMS > Datomic vs. Drizzle vs. ObjectBox vs. Snowflake

System Properties Comparison Datomic vs. Drizzle vs. ObjectBox vs. Snowflake

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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.

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

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

Primary database model

Relational DBMS

Object oriented DBMS
Vector DBMS

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	1.08
Rank	#179	Overall
	#6	Object oriented DBMS
	#9	Vector DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

www.datomic.com

github.com/objectbox
objectbox.io

www.snowflake.com

Technical documentation

docs.datomic.com

docs.objectbox.io

docs.snowflake.net/manuals/index.html

Developer

Cognitect

Drizzle project, originally started by Brian Aker

ObjectBox Limited

Snowflake Computing Inc.

Initial release

2012

2008

2017

2014

Current release

1.0.7180, July 2024

7.2.4, September 2012

4.0 (May 2024)

License

Commercial or Open Source

commercial

limited edition free

Open Source

GNU GPL

Bindings are released under Apache 2.0

Apache License 2.0

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

Java, Clojure

C++

C and C++

Server operating systems

All OS with a Java VM

FreeBSD
Linux
OS X

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

hosted

Data scheme

yes

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

Typing

predefined data types such as float or date

yes

yes, plus "flex" map-like types

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

Proprietary native API

CLI Client
JDBC
ODBC

Supported programming languages

Clojure
Java

C
C++
Java
PHP

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

user defined functions

Triggers

By using transaction functions

hooks for callbacks inside the server can be used.

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

none

yes

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

Data sync between devices allowing occasional connected databases to work completely offline

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

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

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

yes

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

More information provided by the system vendor

News

MongoDB Realm & Device Sync alternatives – ObjectBox
17 September 2024

Local AI – what it is and why we need it
11 September 2024

First on-device Vector Database (aka Semantic Index) for iOS
24 July 2024

Retrieval Augmented Generation (RAG) with vector databases: Expanding AI Capabilities
18 June 2024

The on-device Vector Database for Android and Java
29 May 2024

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