DBMS > BigchainDB vs. OrigoDB vs. Tarantool vs. Transbase vs. YTsaurus

System Properties Comparison BigchainDB vs. OrigoDB vs. Tarantool vs. Transbase vs. YTsaurus

Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

A fully ACID in-memory object graph database

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

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

YTsaurus is an open source platform for distributed storage and processing.

Primary database model

Document store

Document store
Object oriented DBMS

Document store
Key-value store
Relational DBMS

Relational DBMS

Document store
Key-value store

Secondary database models

Spatial DBMS

with Tarantool/GIS extension

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

Score	0.76
Rank	#216	Overall
	#36	Document stores

Score	0.00
Rank	#385	Overall
	#54	Document stores
	#21	Object oriented DBMS

Score	1.63
Rank	#139	Overall
	#25	Document stores
	#24	Key-value stores
	#65	Relational DBMS

Score	0.05
Rank	#355	Overall
	#150	Relational DBMS

Score	0.15
Rank	#323	Overall
	#44	Document stores
	#47	Key-value stores

Website

www.bigchaindb.com

origodb.com

www.tarantool.io

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

ytsaurus.tech

Technical documentation

bigchaindb.readthedocs.io/en/latest

origodb.com/docs

www.tarantool.io/en/doc

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

ytsaurus.tech/docs/en

Developer

Robert Friberg et al

Transaction Software GmbH

Yandex

Initial release

2016

2009

under the name LiveDB

2008

1987

2023

Current release

2.10.0, May 2022

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

commercial

free development license

Open Source

Apache License, Version 2.0

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

Python

C and C++

C++

Server operating systems

Linux

Linux
Windows

BSD
Linux
macOS

FreeBSD
Linux
macOS
Solaris
Windows

Ubuntu

Data scheme

schema-free

yes

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

yes

Typing

predefined data types such as float or date

User defined using .NET types and collections

string, double, decimal, uuid, integer, blob, boolean, datetime

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

Full-featured ANSI SQL support

yes

YQL, an SQL-based language, is supported

APIs and other access methods

CLI Client
RESTful HTTP API

.NET Client API
HTTP API
LINQ

Open binary protocol

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

.Net

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

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

C++
Go
Java
JavaScript
Python

Server-side scripts

Stored procedures

yes

Lua, C and SQL stored procedures

yes

Triggers

yes

Domain Events

yes, before/after data modification events, on replication events, client session events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Immediate Consistency

Foreign keys

Referential integrity

depending on model

yes

Transaction concepts

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

ACID

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

Write ahead log

yes, write ahead logging

yes

In-memory capabilities

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

yes

yes, full featured in-memory storage engine with persistence

User concepts

Access control

yes

Role based authorization

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

fine grained access rights according to SQL-standard

Access Control Lists

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More resources

DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021, Vladimir Perepelytsya, Tarantool (sponsor)

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Recent citations in the news

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