DBMS > Apache Impala vs. EsgynDB vs. OrientDB vs. Sequoiadb

System Properties Comparison Apache Impala vs. EsgynDB vs. OrientDB vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

Multi-model DBMS (Document, Graph, Key/Value)

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store

Document store
Relational 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	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

www.orientdb.com/docs/last/index.html

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Esgyn

OrientDB LTD; CallidusCloud; SAP

Sequoiadb Ltd.

Initial release

2013

2015

2010

2013

Current release

4.1.0, June 2022

3.2.29, March 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache version 2

Open Source

Server: AGPL; Client: Apache V2

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++, Java

Java

C++

Server operating systems

Linux

All OS with a Java JDK (>= JDK 6)

Linux

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

SQL-like query language, no joins

SQL-like query language

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

proprietary protocol using JSON

Supported programming languages

All languages supporting JDBC/ODBC

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java Stored Procedures

Java, Javascript

JavaScript

Triggers

Hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication between multi datacenters

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

ACID

Document is locked during a transaction

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

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

simple password-based access control

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More resources

DB-Engines blog posts

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

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Recent citations in the news

Cloudera creates observability tool to help enterprises manage cloud costs
6 June 2023, SiliconANGLE 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

provided by Google News

The 12 Best Graph Databases to Consider for 2024
22 October 2023, Solutions Review

OrientDB: A Flexible and Scalable Multi-Model NoSQL DBMS
21 January 2022, Open Source For You

Comparing Graph Databases II. Part 2: ArangoDB, OrientDB, and… | by Sam Bell
20 September 2019, Towards Data Science

ArangoDB raises $10 million for NoSQL database management
14 March 2019, VentureBeat

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11 May 2021, TechTarget

provided by Google News

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