DBMS > Apache Impala vs. BigchainDB vs. Heroic vs. HyperSQL

System Properties Comparison Apache Impala vs. BigchainDB vs. Heroic vs. HyperSQL

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Primary database model

Secondary database models

Document store

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

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	3.90
Rank	#85	Overall
	#46	Relational DBMS

Website

impala.apache.org

www.bigchaindb.com

github.com/spotify/heroic

hsqldb.org

Technical documentation

impala.apache.org/impala-docs.html

bigchaindb.readthedocs.io/en/latest

spotify.github.io/heroic

hsqldb.org/web/hsqlDocsFrame.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Spotify

Initial release

2013

2016

2014

2001

Current release

4.1.0, June 2022

2.7.2, June 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

AGPL v3

Open Source

Apache 2.0

Open Source

based on BSD license

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++

Python

Java

Server operating systems

Linux

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Data scheme

yes

schema-free

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

via Elasticsearch

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

CLI Client
RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Go
Haskell
Java
JavaScript
Python
Ruby

All languages supporting JDBC/ODBC
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

none

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

Eventual Consistency
Immediate Consistency

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

yes,with MongoDB ord RethinkDB

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

yes

fine grained access rights according to SQL-standard

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More resources

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