DBMS > EventStoreDB vs. Riak TS vs. Tarantool vs. TerminusDB vs. YottaDB

System Properties Comparison EventStoreDB vs. Riak TS vs. Tarantool vs. TerminusDB vs. YottaDB

Editorial information provided by DB-Engines

Name

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

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

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

A fast and solid embedded Key-value store

Primary database model

Event Store

Time Series DBMS

Document store
Key-value store
Relational DBMS

Graph DBMS

Key-value store

Secondary database models

Spatial DBMS

with Tarantool/GIS extension

Document store
RDF store

Relational DBMS

using the Octo plugin

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

Score	1.07
Rank	#181	Overall
	#1	Event Stores

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

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

Score	0.19
Rank	#311	Overall
	#27	Graph DBMS

Score	0.21
Rank	#309	Overall
	#43	Key-value stores

Website

Technical documentation

developers.eventstore.com

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

www.tarantool.io/en/doc

terminusdb.github.io/terminusdb/#

yottadb.com/resources/documentation

Developer

Event Store Limited

Open Source, formerly Basho Technologies

DataChemist Ltd.

YottaDB, LLC

Initial release

2012

2015

2008

2018

2001

Current release

21.2, February 2021

3.0.0, September 2022

2.10.0, May 2022

11.0.0, January 2023

License

Commercial or Open Source

Open Source

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

Open Source

GPL V3

Open Source

AGPL 3.0

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

Erlang

C and C++

Prolog, Rust

Server operating systems

Linux
Windows

Linux
OS X

BSD
Linux
macOS

Linux

Docker
Linux

Data scheme

schema-free

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

yes

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

restricted

yes

SQL

Support of SQL

yes, limited

Full-featured ANSI SQL support

SQL-like query language (WOQL)

by using the Octo plugin

APIs and other access methods

HTTP API
Native Erlang Interface

Open binary protocol

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

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

JavaScript
Python

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

Erlang

Lua, C and SQL stored procedures

yes

Triggers

yes

pre-commit hooks and post-commit hooks

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.

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

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

Journaling Streams

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

Foreign keys

Referential integrity

links between datasets can be stored

yes

Transaction concepts

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

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

ACID

optimistic locking

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 journaling

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

yes

User concepts

Access control

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

Role-based access control

Users and groups based on OS-security mechanisms

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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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