DBMS > Amazon DocumentDB vs. Datomic vs. HBase vs. InterSystems Caché vs. RocksDB

System Properties Comparison Amazon DocumentDB vs. Datomic vs. HBase vs. InterSystems Caché vs. RocksDB

Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

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

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

Wide-column store based on Apache Hadoop and on concepts of BigTable

A multi-model DBMS and application server

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Document store

Relational DBMS

Wide column store

Key-value store
Object oriented DBMS
Relational DBMS

Key-value store

Secondary database models

Document store

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

aws.amazon.com/documentdb

www.datomic.com

hbase.apache.org

www.intersystems.com/products/cache

rocksdb.org

Technical documentation

aws.amazon.com/documentdb/resources

docs.datomic.com

hbase.apache.org/book.html

docs.intersystems.com

github.com/facebook/rocksdb/wiki

Developer

Cognitect

Apache Software Foundation

Apache top-level project, originally developed by Powerset

InterSystems

Facebook, Inc.

Initial release

2019

2012

2008

1997

2013

Current release

1.0.6735, June 2023

2.3.4, January 2021

2018.1.4, May 2020

8.11.4, April 2024

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache version 2

commercial

Open Source

BSD

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

Java

C++

Server operating systems

hosted

All OS with a Java VM

Linux
Unix
Windows

using Cygwin

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

yes

schema-free, schema definition possible

depending on used data model

schema-free

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

RESTful HTTP API

Java API
RESTful HTTP API
Thrift

.NET Client API
JDBC
ODBC
RESTful HTTP API

C++ API
Java API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Clojure
Java

C
C#
C++
Groovy
Java
PHP
Python
Scala

C#
C++
Java

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

Coprocessors in Java

yes

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

But extensive use of caching in the application peers

Multi-source replication
Source-replica replication

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document operations

ACID

Single row ACID (across millions of columns)

ACID

yes

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

Access rights for users and roles

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Access rights for users, groups and roles

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