DBMS > EXASOL vs. SAP HANA vs. StarRocks vs. VoltDB

System Properties Comparison EXASOL vs. SAP HANA vs. StarRocks vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

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	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.93
Rank	#198	Overall
	#93	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

www.exasol.com

www.sap.com/products/hana.html

www.starrocks.io

www.voltdb.com

Technical documentation

www.exasol.com/resources

help.sap.com/hana

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

docs.voltdb.com

Developer

Exasol

SAP

The Linux Foundation

since Feb 2023

VoltDB Inc.

Initial release

2000

2010

2020

2010

Current release

2.0 SPS07 (April 4, 2023), April 2023

2.5.3, March 2023

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

C++, Java

Java, C++

Server operating systems

Appliance or cloud-service

Linux

Linux
OS X

for development

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

yes

only a subset of SQL 99

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

JDBC
ODBC

JDBC
MySQL protocol

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Java
Lua
Python
R

Java

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

SQLScript, R

user defined functions

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

horizontal partitioning (by range and hash)

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

yes

Role based access control and fine grained access rights

Users and roles with access to stored procedures

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