DBMS > jBASE vs. Kinetica vs. LeanXcale vs. Milvus vs. SAP HANA

System Properties Comparison jBASE vs. Kinetica vs. LeanXcale vs. Milvus vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

A robust multi-value DBMS comprising development tools and middleware

Fully vectorized database across both GPUs and CPUs

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

A DBMS designed for efficient storage of vector data and vector similarity searches

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

Primary database model

Multivalue DBMS

Relational DBMS

Key-value store
Relational DBMS

Vector DBMS

Relational DBMS

Secondary database models

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	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

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

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

www.kinetica.com

www.leanxcale.com

milvus.io

www.sap.com/products/hana.html

Technical documentation

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

docs.kinetica.com

milvus.io/docs/overview.md

help.sap.com/hana

Developer

Rocket Software (formerly Zumasys)

Kinetica

LeanXcale

SAP

Initial release

1991

2012

2015

2019

2010

Current release

5.7

7.1, August 2021

2.3.4, January 2024

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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.

Zilliz Cloud – Cloud-native service for Milvus

Implementation language

C, C++

C++, Go

Server operating systems

AIX
Linux
Windows

Linux

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Appliance or cloud-service

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

optional

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.

yes

Secondary indexes

yes

SQL

Support of SQL

Embedded SQL for jBASE in BASIC

SQL-like DML and DDL statements

yes

through Apache Derby

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

JDBC
ODBC
RESTful HTTP API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

RESTful HTTP API

JDBC
ODBC

Supported programming languages

.Net
Basic
Jabbascript
Java

C++
Java
JavaScript (Node.js)
Python

C
Java
Scala

C++
Go
Java
JavaScript (Node.js)
Python

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

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

GPU vRAM or System RAM

yes

User concepts

Access control

Access rights can be defined down to the item level

Access rights for users and roles on table level

Role based access control and fine grained access rights

yes

More information provided by the system vendor

Specific characteristics

Milvus is an open-source and cloud-native vector database built for production-ready...
» more

Competitive advantages

Highly available, versatile, and robust with millisecond latency. Supports batch...
» more

Typical application scenarios

RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more

Key customers

Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more

Market metrics

As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise...
» more

Licensing and pricing models

Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.