DBMS > Apache Impala vs. EventStoreDB vs. Hyprcubd

System Properties Comparison Apache Impala vs. EventStoreDB vs. Hyprcubd

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Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

Analytic DBMS for Hadoop

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Serverless Time Series DBMS

Primary database model

Relational DBMS

Event Store

Time Series DBMS

Secondary database models

Document store

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

Score	12.57
Rank	#40	Overall
	#24	Relational DBMS

Score	1.04
Rank	#181	Overall
	#1	Event Stores

Website

impala.apache.org

www.eventstore.com

hyprcubd.com (offline)

Technical documentation

impala.apache.org/impala-docs.html

developers.eventstore.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Event Store Limited

Hyprcubd, Inc.

Initial release

2013

2012

Current release

4.1.0, June 2022

21.2, February 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Server operating systems

Linux

Linux
Windows

hosted

Data scheme

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, 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

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

JDBC
ODBC

gRPC (https)

Supported programming languages

All languages supporting JDBC/ODBC

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

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

Foreign keys

Referential integrity

Transaction concepts

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

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

token access

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More resources

Recent citations in the news

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

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Tabular, the vendor-neutral data store based on Apache Iceberg, raises $26M in funding
19 September 2023, SiliconANGLE News

Apache Iceberg Changes Everything: What's Underneath?
28 August 2023, Spiceworks News and Insights

Introduction to Bigdata and Hadoop Ecosystem | by Arpita Mishra | Jun, 2024
7 June 2024, Medium

provided by Google News

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