DBMS > BigObject vs. Cachelot.io vs. RavenDB vs. SwayDB vs. Ultipa

System Properties Comparison BigObject vs. Cachelot.io vs. RavenDB vs. SwayDB vs. Ultipa

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

In-memory caching system

Open Source Operational and Transactional Enterprise NoSQL Document Database

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	0.04
Rank	#388	Overall
	#62	Key-value stores

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Score	0.19
Rank	#330	Overall
	#30	Graph DBMS

Website

Technical documentation

docs.bigobject.io

ravendb.net/docs

www.ultipa.com/document

Developer

BigObject, Inc.

Hibernating Rhinos

Simer Plaha

Ultipa

Initial release

2015

2010

2018

2019

Current release

5.4, July 2022

License

Commercial or Open Source

commercial

free community edition available

Open Source

Simplified BSD License

Open Source

AGPL version 3, commercial license available

Open Source

GNU Affero GPL V3.0

commercial

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++

Scala

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

FreeBSD
Linux
OS X

Linux
macOS
Raspberry Pi
Windows

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language (RQL)

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

Memcached protocol

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

RESTful HTTP API

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

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

Java
Kotlin
Scala

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

automatically between fact table and dimension tables

Transaction concepts

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

ACID, Cluster-wide transaction available

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

Authorization levels configured per client per database

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