DBMS > Apache Impala vs. Transbase vs. Transwarp Hippo vs. VelocityDB

System Properties Comparison Apache Impala vs. Transbase vs. Transwarp Hippo vs. VelocityDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

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

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Relational DBMS

Vector DBMS

Graph DBMS
Object oriented DBMS

Secondary database models

Document store

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Score	0.05
Rank	#386	Overall
	#14	Vector DBMS

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Website

impala.apache.org

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

www.transwarp.cn/en/subproduct/hippo

velocitydb.com

Technical documentation

impala.apache.org/impala-docs.html

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

velocitydb.com/UserGuide

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Transaction Software GmbH

VelocityDB Inc

Initial release

2013

1987

2023

2011

Current release

4.1.0, June 2022

Transbase 8.3, 2022

1.0, May 2023

7.x

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free development license

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

C and C++

C++

Server operating systems

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Linux
macOS

Any that supports .NET

Data scheme

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

RESTful HTTP API

.Net

Supported programming languages

All languages supporting JDBC/ODBC

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

C++
Java
Python

.Net

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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.

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

Based on Windows Authentication

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More resources

Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

provided by Google News

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