DBMS > SpaceTime vs. Tkrzw vs. Transwarp Hippo vs. Yaacomo

System Properties Comparison SpaceTime vs. Tkrzw vs. Transwarp Hippo vs. Yaacomo

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Editorial information provided by DB-Engines

Name

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

Description

SpaceTime is a spatio-temporal DBMS with a focus on performance.

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

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

Primary database model

Secondary database models

Relational DBMS

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

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Score	0.05
Rank	#386	Overall
	#14	Vector DBMS

Website

www.mireo.com/spacetime

dbmx.net/tkrzw

www.transwarp.cn/en/subproduct/hippo

yaacomo.com

Developer

Mireo

Mikio Hirabayashi

Q2WEB GmbH

Initial release

2020

2023

2009

Current release

0.9.3, August 2020

1.0, May 2023

License

Commercial or Open Source

commercial

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

Android
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

yes

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

Supported programming languages

C#
C++
Python

C++
Java
Python
Ruby

C++
Java
Python

Server-side scripts

Stored procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Fixed-grid hypercubes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Real-time block device replication (DRBD)

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

yes

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

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