DBMS > JaguarDB vs. Sequoiadb vs. Tarantool vs. Tkrzw vs. Yaacomo

System Properties Comparison JaguarDB vs. Sequoiadb vs. Tarantool vs. Tkrzw vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Performant, highly scalable DBMS for AI and IoT applications

NewSQL database with distributed OLTP and SQL

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

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Key-value store
Vector DBMS

Document store
Relational DBMS

Document store
Key-value store
Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

with Tarantool/GIS extension

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

Score	0.00
Rank	#385	Overall
	#61	Key-value stores
	#16	Vector DBMS

Score	0.42
Rank	#263	Overall
	#41	Document stores
	#121	Relational DBMS

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

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Website

yaacomo.com

Technical documentation

www.jaguardb.com/support.html

www.sequoiadb.com/en/index.php?m=Files&a=index

www.tarantool.io/en/doc

Developer

DataJaguar, Inc.

Sequoiadb Ltd.

Mikio Hirabayashi

Q2WEB GmbH

Initial release

2015

2013

2008

2020

2009

Current release

3.3 July 2023

2.10.0, May 2022

0.9.3, August 2020

License

Commercial or Open Source

Open Source

GPL V3.0

Open Source

Server: AGPL; Client: Apache V2

Open Source

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

Open Source

Apache Version 2.0

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++

the server part. Clients available in other languages

C++

C and C++

C++

Server operating systems

Linux

BSD
Linux
macOS

Linux
macOS

Android
Linux
Windows

Data scheme

yes

schema-free

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

schema-free

yes

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

Full-featured ANSI SQL support

yes

APIs and other access methods

JDBC
ODBC

proprietary protocol using JSON

Open binary protocol

JDBC
ODBC

Supported programming languages

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

.Net
C++
Java
PHP
Python

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

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

JavaScript

Lua, C and SQL stored procedures

Triggers

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

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

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

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Document is locked during a transaction

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

yes

using specific database classes

yes

User concepts

Access control

rights management via user accounts

simple password-based 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

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

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

show all

Recent citations in the news

Deploying Tarantool Cartridge applications with zero effort (Part 1)
16 December 2019, Хабр

VShard — horizontal scaling in Tarantool
7 March 2019, Хабр

Accelerating PHP connectors for Tarantool using Async, Swoole, and Parallel
18 December 2019, Хабр

provided by Google News

Share this page