DBMS > StarRocks vs. Transbase vs. Vertica

System Properties Comparison StarRocks vs. Transbase vs. Vertica

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Editorial information provided by DB-Engines

Name

Description

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

Forked from Apache Doris

A resource-optimized, high-performance, universally applicable RDBMS

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Relational DBMS

Column oriented

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.94
Rank	#188	Overall
	#86	Relational DBMS

Score	0.01
Rank	#378	Overall
	#155	Relational DBMS

Score	9.78
Rank	#42	Overall
	#26	Relational DBMS

Website

www.starrocks.io

www.transaction.de/en/products/transbase.html

www.vertica.com

Technical documentation

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

www.transaction.de/en/products/transbase/features.html

vertica.com/documentation

Developer

The Linux Foundation

since Feb 2023

Transaction Software GmbH

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2020

1987

2005

Current release

3.3, June 2024

Transbase 8.3, 2022

12.0.3, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free development license

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++, Java

C and C++

C++

Server operating systems

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Linux

Data scheme

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

JDBC
MySQL protocol

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

Java

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

user defined functions

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range and hash)

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

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

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.

User concepts

Access control

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources

Recent citations in the news

StarRocks analytical DB heads to Linux Foundation
14 February 2023, VentureBeat

StarRocks brings open source OLAP database to the cloud
14 July 2022, TechTarget

StarRocks Launches the Industry's Fastest, Cloud Native, Real-time Analytics Engine
14 July 2022, GlobeNewswire

Enabling Real-Time Analytics at Data Summit 2024
8 May 2024, Database Trends and Applications

CelerData: How This Company Reduces Data Migration And Direct Analysis Costs In Data Lakes
21 December 2023, Pulse 2.0

provided by Google News

Introducing the Future of Data Analysis: A Revolutionary Tool for Vertica Users
25 October 2024, OpenText Blogs

Leveraging Vertica Performance by Reducing CPU System Calls
23 January 2025, Taboola.com

New browser-based query editor for OpenText Core Analytics Database accelerates and simplifies querying your data
25 November 2024, OpenText Blogs

Querying a Vertica data source in Amazon Athena using the Athena Federated Query SDK
11 February 2021, Amazon Web Services (AWS)

Vertica on Kubernetes
20 June 2024, OpenText Blogs

provided by Google News

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