DBMS > Apache Impala vs. HugeGraph vs. OrigoDB

System Properties Comparison Apache Impala vs. HugeGraph vs. OrigoDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A fast-speed and highly-scalable Graph DBMS

A fully ACID in-memory object graph database

Primary database model

Relational DBMS

Graph DBMS

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	0.13
Rank	#336	Overall
	#32	Graph DBMS

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

Website

impala.apache.org

github.com/hugegraph
hugegraph.apache.org

origodb.com

Technical documentation

impala.apache.org/impala-docs.html

hugegraph.apache.org/docs

origodb.com/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Baidu

Robert Friberg et al

Initial release

2013

2018

2009

under the name LiveDB

Current release

4.1.0, June 2022

0.9

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

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++

Java

Server operating systems

Linux

Linux
macOS
Unix

Linux
Windows

Data scheme

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

also supports composite index and range index

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
TinkerPop Gremlin

.NET Client API
HTTP API
LINQ

Supported programming languages

All languages supporting JDBC/ODBC

Groovy
Java
Python

.Net

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

asynchronous Gremlin script jobs

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

depending on used storage backend, e.g. Cassandra and HBase

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

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

Users, roles and permissions

Role based authorization

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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

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

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

provided by Google News

Critical Apache HugeGraph Flaw Let Attackers Execute Remote Code
23 April 2024, GBHackers

provided by Google News

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