DBMS > Hyprcubd vs. NuoDB vs. RocksDB vs. Sphinx vs. VoltDB

System Properties Comparison Hyprcubd vs. NuoDB vs. RocksDB vs. Sphinx vs. VoltDB

Editorial information provided by DB-Engines

Name

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

Description

Serverless Time Series DBMS

NuoDB is a webscale distributed database that supports SQL and ACID transactions

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

Open source search engine for searching in data from different sources, e.g. relational databases

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

Primary database model

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

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

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

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

hyprcubd.com (offline)

www.3ds.com/nuodb-distributed-sql-database

rocksdb.org

sphinxsearch.com

www.voltdb.com

Technical documentation

doc.nuodb.com

github.com/facebook/rocksdb/wiki

sphinxsearch.com/docs

docs.voltdb.com

Developer

Hyprcubd, Inc.

Dassault Systèmes

originally NuoDB, Inc.

Facebook, Inc.

Sphinx Technologies Inc.

VoltDB Inc.

Initial release

2013

2001

2010

Current release

8.11.4, April 2024

3.5.1, February 2023

11.3, April 2022

License

Commercial or Open Source

commercial

limited edition free

Open Source

BSD

Open Source

GPL version 2, commercial licence available

Open Source

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

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

C++

Java, C++

Server operating systems

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X

for development

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

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language (SphinxQL)

yes

only a subset of SQL 99

APIs and other access methods

gRPC (https)

ADO.NET
JDBC
ODBC

C++ API
Java API

Proprietary protocol

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

C
C++
Go
Java
Perl
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Java, SQL

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

data is dynamically stored/cached on the nodes where it is read/written

horizontal partitioning

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Managed transparently by NuoDB

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

tunable commit protocol

yes

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

yes

Snapshots and command logging

In-memory capabilities

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

yes

Temporary table

yes

User concepts

Access control

token access

Standard SQL roles/ privileges, Administrative Users

Users and roles with access to stored procedures

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