DBMS > Amazon DocumentDB vs. Apache Druid vs. LMDB vs. OrientDB vs. Snowflake

System Properties Comparison Amazon DocumentDB vs. Apache Druid vs. LMDB vs. OrientDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

Primary database model

Document store

Relational DBMS
Time Series DBMS

Key-value store

Document store
Graph DBMS
Key-value store

Relational DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

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

Website

aws.amazon.com/documentdb

druid.apache.org

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

orientdb.org

www.snowflake.com

Technical documentation

aws.amazon.com/documentdb/resources

druid.apache.org/docs/latest/design

www.lmdb.tech/doc

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

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation and contributors

Symas

OrientDB LTD; CallidusCloud; SAP

Snowflake Computing Inc.

Initial release

2019

2012

2011

2010

2014

Current release

29.0.1, April 2024

0.9.32, January 2024

3.2.29, March 2024

License

Commercial or Open Source

commercial

Open Source

Apache license v2

Open Source

Apache version 2

commercial

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

Server operating systems

hosted

Linux
OS X
Unix

Linux
Unix
Windows

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

hosted

Data scheme

schema-free

yes

schema-less columns are supported

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)

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 for querying

SQL-like query language, no joins

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JDBC
RESTful HTTP/JSON API

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

CLI Client
JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.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

Server-side scripts

Stored procedures

Java, Javascript

user defined functions

Triggers

Hooks

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

manual/auto, time-based

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

yes, via HDFS, S3 or other storage engines

none

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

relationship in graphs

yes

Transaction concepts

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

Atomic single-document operations

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 and roles

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

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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