DBMS > EJDB vs. Hive vs. IBM Db2 warehouse vs. Sequoiadb

System Properties Comparison EJDB vs. Hive vs. IBM Db2 warehouse vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Cloud-based data warehousing service

NewSQL database with distributed OLTP and SQL

Primary database model

Document store

Relational DBMS

Document store
Relational DBMS

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	1.37
Rank	#160	Overall
	#74	Relational DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Website

github.com/Softmotions/ejdb

hive.apache.org

www.ibm.com/products/db2/warehouse

www.sequoiadb.com

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

cwiki.apache.org/confluence/display/Hive/Home

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

Developer

Softmotions

Apache Software Foundation

initially developed by Facebook

IBM

Sequoiadb Ltd.

Initial release

2012

2014

2013

Current release

3.1.3, April 2022

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Apache Version 2

commercial

Open Source

Server: AGPL; Client: Apache V2

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

Java

C++

Server operating systems

server-less

All OS with a Java VM

hosted

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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.

Import/export of XML data possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like query language

APIs and other access methods

in-process shared library

JDBC
ODBC
Thrift

.NET Client API
JDBC
ODBC
OLE DB

proprietary protocol using JSON

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C++
Java
PHP
Python

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

PL/SQL, SQL PL

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

yes

Source-replica replication

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

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

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

Read/Write Locking

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.

yes

User concepts

Access control

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

simple password-based access control

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