DBMS > Apache Impala vs. EsgynDB vs. Hypertable vs. OrigoDB

System Properties Comparison Apache Impala vs. EsgynDB vs. Hypertable vs. OrigoDB

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Analytic DBMS for Hadoop

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

An open source BigTable implementation based on distributed file systems such as Hadoop

A fully ACID in-memory object graph database

Primary database model

Relational DBMS

Wide column store

Document store
Object oriented DBMS

Secondary database models

Document store

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

impala.apache.org

www.esgyn.cn

origodb.com

Technical documentation

impala.apache.org/impala-docs.html

origodb.com/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Esgyn

Hypertable Inc.

Robert Friberg et al

Initial release

2013

2015

2009

under the name LiveDB

Current release

4.1.0, June 2022

0.9.8.11, March 2016

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

GNU version 3. Commercial license available

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C++, Java

C++

Server operating systems

Linux

Linux
OS X
Windows

an inofficial Windows port is available

Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

C++ API
Thrift

.NET Client API
HTTP API
LINQ

Supported programming languages

All languages supporting JDBC/ODBC

All languages supporting JDBC/ODBC/ADO.Net

C++
Java
Perl
PHP
Python
Ruby

.Net

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java Stored Procedures

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication between multi datacenters

selectable replication factor on file system level

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

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

Write ahead log

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 authorization

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More resources

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