DBMS > BigObject vs. Hyprcubd vs. RavenDB vs. VoltDB vs. Yaacomo

System Properties Comparison BigObject vs. Hyprcubd vs. RavenDB vs. VoltDB vs. Yaacomo

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Analytic DBMS for real-time computations and queries

Serverless Time Series DBMS

Open Source Operational and Transactional Enterprise NoSQL Document Database

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Time Series DBMS

Document store

Relational DBMS

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

bigobject.io

hyprcubd.com (offline)

ravendb.net

www.voltdb.com

yaacomo.com

Technical documentation

docs.bigobject.io

ravendb.net/docs

docs.voltdb.com

Developer

BigObject, Inc.

Hyprcubd, Inc.

Hibernating Rhinos

VoltDB Inc.

Q2WEB GmbH

Initial release

2015

2010

2009

Current release

5.4, July 2022

11.3, April 2022

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

AGPL version 3, commercial license available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java, C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

hosted

Linux
macOS
Raspberry Pi
Windows

Linux
OS X

for development

Android
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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

SQL-like query language (RQL)

yes

only a subset of SQL 99

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

gRPC (https)

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

Java API
JDBC
RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

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

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Lua

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

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

FOREIGN KEY constraints are not supported

yes

Transaction concepts

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

ACID, Cluster-wide transaction available

ACID

Transactions are executed single-threaded within stored procedures

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes

Snapshots and command logging

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

token access

Authorization levels configured per client per database

Users and roles with access to stored procedures

fine grained access rights according to SQL-standard

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