DBMS > RavenDB vs. Tarantool vs. WakandaDB vs. YDB

System Properties Comparison RavenDB vs. Tarantool vs. WakandaDB vs. YDB

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Editorial information provided by DB-Engines

Name

Description

Open Source Operational and Transactional Enterprise NoSQL Document Database

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

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

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

Document store

Document store
Key-value store
Relational DBMS

Object oriented DBMS

Document store
Relational DBMS

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

Spatial DBMS

with Tarantool/GIS extension

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

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	1.72
Rank	#144	Overall
	#25	Document stores
	#25	Key-value stores
	#66	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Score	0.35
Rank	#278	Overall
	#43	Document stores
	#127	Relational DBMS

Website

ravendb.net

www.tarantool.io

wakanda.github.io

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

Technical documentation

ravendb.net/docs

www.tarantool.io/en/doc

wakanda.github.io/doc

ydb.tech/en/docs

Developer

Hibernating Rhinos

Wakanda SAS

Yandex

Initial release

2010

2008

2012

2019

Current release

5.4, July 2022

2.10.0, May 2022

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

AGPL version 3, commercial license available

Open Source

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

Open Source

AGPLv3, extended commercial license available

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 and C++

C++, JavaScript

Server operating systems

Linux
macOS
Raspberry Pi
Windows

BSD
Linux
macOS

Linux
OS X
Windows

Linux

Data scheme

schema-free

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

yes

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (RQL)

Full-featured ANSI SQL support

SQL-like query language (YQL)

APIs and other access methods

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

Open binary protocol

RESTful HTTP API

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

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

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

JavaScript

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

yes

Lua, C and SQL stored procedures

yes

Triggers

yes

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

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

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

none

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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.

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

yes

Transaction concepts

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

ACID, Cluster-wide transaction available

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

yes

Durability

Support for making data persistent

yes

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, full featured in-memory storage engine with persistence

User concepts

Access control

Authorization levels configured per client per database

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

yes

Access rights defined for Yandex Cloud users

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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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