DBMS > Brytlyt vs. Datomic vs. InterSystems Caché vs. Riak KV vs. RocksDB

System Properties Comparison Brytlyt vs. Datomic vs. InterSystems Caché vs. Riak KV 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

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

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

A multi-model DBMS and application server

Distributed, fault tolerant key-value store

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

Primary database model

Relational DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Key-value store

Secondary database models

Document store

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

Score	0.38
Rank	#279	Overall
	#126	Relational DBMS

Score	1.76
Rank	#145	Overall
	#66	Relational DBMS

Score	4.44
Rank	#80	Overall
	#9	Key-value stores

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Website

brytlyt.io

www.datomic.com

www.intersystems.com/products/cache

rocksdb.org

Technical documentation

docs.brytlyt.io

docs.datomic.com

docs.intersystems.com

www.tiot.jp/riak-docs/riak/kv/latest

github.com/facebook/rocksdb/wiki

Developer

Brytlyt

Cognitect

InterSystems

OpenSource, formerly Basho Technologies

Facebook, Inc.

Initial release

2016

2012

1997

2009

2013

Current release

5.0, August 2023

1.0.6735, June 2023

2018.1.4, May 2020

3.2.0, December 2022

8.11.4, April 2024

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

Apache version 2, commercial enterprise edition

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++ and CUDA

Java, Clojure

Erlang

C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

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

Linux
OS X

Linux

Data scheme

yes

depending on used data model

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

specific XML-type available, but no XML query functionality.

yes

Secondary indexes

yes

restricted

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP API

.NET Client API
JDBC
ODBC
RESTful HTTP API

HTTP API
Native Erlang Interface

C++ API
Java API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Clojure
Java

C#
C++
Java

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes

Transaction Functions

yes

Erlang

Triggers

yes

By using transaction functions

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding

no "single point of failure"

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

But extensive use of caching in the application peers

Source-replica replication

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

Transaction concepts

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

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

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

yes, using Riak Security

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