DBMS > Lovefield vs. Machbase Neo vs. SAP HANA vs. Transwarp KunDB

System Properties Comparison Lovefield vs. Machbase Neo vs. SAP HANA vs. Transwarp KunDB

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Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

TimeSeries DBMS for AIoT and BigData

In-memory, column based data store. Available as appliance or cloud service

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

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.14
Rank	#341	Overall
	#149	Relational DBMS

Website

google.github.io/lovefield

machbase.com

www.sap.com/products/hana.html

www.transwarp.cn/en/product/kundb

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

machbase.com/dbms

help.sap.com/hana

Developer

Google

Machbase

SAP

Transwarp

Initial release

2014

2013

2010

Current release

2.1.12, February 2017

V8.0, August 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free test version available

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
macOS
Windows

Appliance or cloud-service

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

SQL-like query language

yes

APIs and other access methods

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

JDBC
ODBC

Supported programming languages

JavaScript

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Server-side scripts

Stored procedures

SQLScript, R

yes

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

yes

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, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

volatile and lookup table

yes

User concepts

Access control

simple password-based access control

yes

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