DBMS > DolphinDB vs. Kinetica vs. LeanXcale vs. SAP HANA vs. Yanza

System Properties Comparison DolphinDB vs. Kinetica vs. LeanXcale vs. SAP HANA vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Fully vectorized database across both GPUs and CPUs

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

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

Time Series DBMS for IoT Applications

Primary database model

Time Series DBMS

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

Spatial DBMS
Time Series DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

www.dolphindb.com

www.kinetica.com

www.leanxcale.com

www.sap.com/products/hana.html

yanza.com

Technical documentation

docs.dolphindb.cn/en/help200/index.html

docs.kinetica.com

help.sap.com/hana

Developer

DolphinDB, Inc

Kinetica

LeanXcale

SAP

Yanza

Initial release

2018

2012

2015

2010

2015

Current release

v2.00.4, January 2022

7.1, August 2021

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

free community version available

commercial

free version available

Cloud-based only

Only available as a cloud service

also available as a cloud based service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

C, C++

Server operating systems

Linux
Windows

Linux

Appliance or cloud-service

Windows

Data scheme

yes

schema-free

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

SQL-like DML and DDL statements

yes

through Apache Derby

yes

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

JDBC
ODBC
RESTful HTTP API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

JDBC
ODBC

HTTP API

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

C++
Java
JavaScript (Node.js)
Python

C
Java
Scala

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

user defined functions

SQLScript, R

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

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

GPU vRAM or System RAM

yes

User concepts

Access control

Administrators, Users, Groups

Access rights for users and roles on table level

yes

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