DBMS > Firebolt vs. SAP HANA vs. Transwarp Hippo

System Properties Comparison Firebolt vs. SAP HANA vs. Transwarp Hippo

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Editorial information provided by DB-Engines

Name

Description

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

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

Vector 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	1.73
Rank	#140	Overall
	#63	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.05
Rank	#386	Overall
	#16	Vector DBMS

Website

www.firebolt.io

www.sap.com/products/hana.html

www.transwarp.cn/en/subproduct/hippo

Technical documentation

docs.firebolt.io

help.sap.com/hana

Developer

Firebolt Analytics Inc.

SAP

Initial release

2020

2010

2023

Current release

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

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Implementation language

C++

Server operating systems

hosted

Appliance or cloud-service

Linux
macOS

Data scheme

yes

Typing

predefined data types such as float or date

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

SQL

Support of SQL

yes

APIs and other access methods

.Net
ODBC
RESTful HTTP API

JDBC
ODBC

RESTful HTTP API

Supported programming languages

Go
JavaScript (Node.js)
Python

C++
Java
Python

Server-side scripts

Stored procedures

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

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

In-memory capabilities

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

yes

User concepts

Access control

yes

Role based access control and fine grained access rights

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