DBMS > Brytlyt vs. HarperDB vs. NuoDB vs. Riak KV vs. SpaceTime

System Properties Comparison Brytlyt vs. HarperDB vs. NuoDB vs. Riak KV vs. SpaceTime

Editorial information provided by DB-Engines

Name

Description

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

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

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

Distributed, fault tolerant key-value store

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

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

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Website

brytlyt.io

www.harperdb.io

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

www.mireo.com/spacetime

Technical documentation

docs.brytlyt.io

docs.harperdb.io/docs

doc.nuodb.com

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

Developer

Brytlyt

HarperDB

Dassault Systèmes

originally NuoDB, Inc.

OpenSource, formerly Basho Technologies

Mireo

Initial release

2016

2017

2013

2009

2020

Current release

5.0, August 2023

3.1, August 2021

3.2.0, December 2022

License

Commercial or Open Source

commercial

free community edition available

commercial

limited edition free

Open Source

Apache version 2, commercial enterprise edition

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, C++ and CUDA

Node.js

C++

Erlang

C++

Server operating systems

Linux
OS X
Windows

Linux
OS X

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Linux
OS X

Linux

Data scheme

yes

dynamic schema

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON data types

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

restricted

SQL

Support of SQL

yes

SQL-like data manipulation statements

yes

A subset of ANSI SQL is implemented

APIs and other access methods

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

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

ADO.NET
JDBC
ODBC

HTTP API
Native Erlang Interface

RESTful HTTP API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

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

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++
Python

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

Custom Functions

since release 3.1

Java, SQL

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

A table resides as a whole on one (or more) nodes in a cluster

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

Sharding

no "single point of failure"

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

the nodes on which a table resides can be defined

yes

Managed transparently by NuoDB

selectable replication factor

Real-time block device replication (DRBD)

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

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

Atomic execution of specific operations

ACID

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes

In-memory capabilities

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

yes

Temporary table

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

Standard SQL roles/ privileges, Administrative Users

yes, using Riak Security

yes

More information provided by the system vendor

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More resources

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