DBMS > ReductStore vs. Transbase vs. VelocityDB vs. YDB

System Properties Comparison ReductStore vs. Transbase vs. VelocityDB vs. YDB

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Editorial information provided by DB-Engines

Name

Description

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

A resource-optimized, high-performance, universally applicable RDBMS

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Time Series DBMS

Relational DBMS

Graph DBMS
Object oriented DBMS

Document store
Relational DBMS

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

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Score	0.33
Rank	#287	Overall
	#43	Document stores
	#132	Relational DBMS

Website

github.com/reductstore
www.reduct.store

www.transaction.de/en/products/transbase.html

velocitydb.com

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

www.reduct.store/docs

www.transaction.de/en/products/transbase/features.html

velocitydb.com/UserGuide

ydb.tech/en/docs

Developer

ReductStore LLC

Transaction Software GmbH

VelocityDB Inc

Yandex

Initial release

2023

1987

2011

2019

Current release

1.9, March 2024

Transbase 8.3, 2022

7.x

License

Commercial or Open Source

Open Source

Business Source License 1.1

commercial

free development license

commercial

Open Source

Apache 2.0; commercial license available

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++, Rust

C and C++

Server operating systems

Docker
Linux
macOS
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Any that supports .NET

Linux

Data scheme

yes

Flexible Schema (defined schema, partial schema, 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

yes

SQL-like query language (YQL)

APIs and other access methods

HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

.Net

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

C++
JavaScript (Node.js)
Python
Rust

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

.Net

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

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

fine grained access rights according to SQL-standard

Based on Windows Authentication

Access rights defined for Yandex Cloud users

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