DBMS > Sequoiadb vs. Tkrzw vs. Transwarp Hippo

System Properties Comparison Sequoiadb vs. Tkrzw vs. Transwarp Hippo

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Editorial information provided by DB-Engines

Name

Description

NewSQL database with distributed OLTP and SQL

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

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Document store
Relational DBMS

Key-value store

Vector DBMS

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

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

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

Score	0.00
Rank	#385	Overall
	#16	Vector DBMS

Website

www.sequoiadb.com

dbmx.net/tkrzw

www.transwarp.cn/en/subproduct/hippo

Technical documentation

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

Developer

Sequoiadb Ltd.

Mikio Hirabayashi

Initial release

2013

2020

2023

Current release

0.9.3, August 2020

1.0, May 2023

License

Commercial or Open Source

Open Source

Server: AGPL; Client: Apache V2

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

Linux

Linux
macOS

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

Vector, Numeric and String

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

APIs and other access methods

proprietary protocol using JSON

RESTful HTTP API

Supported programming languages

.Net
C++
Java
PHP
Python

C++
Java
Python
Ruby

C++
Java
Python

Server-side scripts

Stored procedures

JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Document is locked during a transaction

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

using specific database classes

yes

User concepts

Access control

simple password-based access control

Role based access control and fine grained access rights

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More resources

Recent citations in the news

10 top vector database options for similarity searches
8 August 2024, TechTarget

provided by Google News

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