DBMS > Kinetica vs. Microsoft Azure Cosmos DB vs. SAP HANA vs. Transwarp Hippo

System Properties Comparison Kinetica vs. Microsoft Azure Cosmos DB vs. SAP HANA vs. Transwarp Hippo

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Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

Globally distributed, horizontally scalable, multi-model database service

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

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Vector DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

Spatial 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	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.05
Rank	#386	Overall
	#15	Vector DBMS

Website

www.kinetica.com

azure.microsoft.com/services/cosmos-db

www.sap.com/products/hana.html

www.transwarp.cn/en/subproduct/hippo

Technical documentation

docs.kinetica.com

learn.microsoft.com/azure/cosmos-db

help.sap.com/hana

Developer

Kinetica

Microsoft

SAP

Initial release

2012

2014

2010

2023

Current release

7.1, August 2021

2.0 SPS07 (April 4, 2023), April 2023

1.0, May 2023

License

Commercial or Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

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

C, C++

C++

Server operating systems

Linux

hosted

Appliance or cloud-service

Linux
macOS

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

Vector, Numeric and String

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

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
ODBC

RESTful HTTP API

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C++
Java
Python

Server-side scripts

Stored procedures

user defined functions

JavaScript

SQLScript, R

Triggers

yes

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

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Implicit feature of the cloud service

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

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 for users and roles on table level

Access rights can be defined down to the item level

yes

Role based access control and fine grained access rights

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