DBMS > Databricks vs. Riak TS vs. SpaceTime vs. Transwarp KunDB

System Properties Comparison Databricks vs. Riak TS vs. SpaceTime vs. Transwarp KunDB

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Editorial information provided by DB-Engines

Name

Description

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

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

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

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Document store
Relational DBMS

Time Series DBMS

Spatial DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	81.08
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Score	0.14
Rank	#341	Overall
	#149	Relational DBMS

Website

www.databricks.com

www.mireo.com/spacetime

www.transwarp.cn/en/product/kundb

Technical documentation

docs.databricks.com

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

Developer

Databricks

Open Source, formerly Basho Technologies

Mireo

Transwarp

Initial release

2013

2015

2020

Current release

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

C++

Server operating systems

hosted

Linux
OS X

Linux

Data scheme

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

schema-free

yes

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

with Databricks SQL

yes, limited

A subset of ANSI SQL is implemented

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HTTP API
Native Erlang Interface

RESTful HTTP API

Supported programming languages

Python
R
Scala

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++
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

Erlang

yes

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Fixed-grid hypercubes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Real-time block device replication (DRBD)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

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

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.

User concepts

Access control

yes

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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