DBMS > Brytlyt vs. Couchbase vs. Ehcache vs. RavenDB vs. SWC-DB

System Properties Comparison Brytlyt vs. Couchbase vs. Ehcache vs. RavenDB vs. SWC-DB

Editorial information provided by DB-Engines

Name

Description

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

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

A widely adopted Java cache with tiered storage options

Open Source Operational and Transactional Enterprise NoSQL Document Database

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

Time Series DBMS

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

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.brytlyt.io

docs.couchbase.com

www.ehcache.org/documentation

ravendb.net/docs

Developer

Brytlyt

Couchbase, Inc.

Terracotta Inc, owned by Software AG

Hibernating Rhinos

Alex Kashirin

Initial release

2016

2011

2009

2010

2020

Current release

5.0, August 2023

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

3.10.0, March 2022

5.4, July 2022

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache Version 2; commercial licenses available

Open Source

AGPL version 3, commercial license available

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++ and CUDA

C, C++, Go and Erlang

Java

C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Linux
macOS
Raspberry Pi
Windows

Linux

Data scheme

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

SQL-like query language (RQL)

SQL-like query language

APIs and other access methods

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

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

JCache

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Proprietary protocol
Thrift

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Java

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes

Triggers

yes

via the TAP protocol

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

by using Terracotta Server

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

including cross data center replication
Source-replica replication

yes

by using Terracotta Server

Multi-source replication

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
Immediate Consistency

selectable on a per-operation basis

Tunable Consistency (Strong, Eventual, Weak)

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

supports JTA and can work as an XA resource

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

In-memory capabilities

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

yes

Ephemeral buckets

yes

User concepts

Access control

fine grained access rights according to SQL-standard

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Authorization levels configured per client per database

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