DBMS > Amazon DocumentDB vs. Apache Impala vs. EJDB vs. Oracle Berkeley DB

System Properties Comparison Amazon DocumentDB vs. Apache Impala vs. EJDB vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Analytic DBMS for Hadoop

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

Widely used in-process key-value store

Primary database model

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Secondary database models

Document store

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Website

aws.amazon.com/documentdb

impala.apache.org

github.com/Softmotions/ejdb

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

aws.amazon.com/documentdb/resources

impala.apache.org/impala-docs.html

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

docs.oracle.com/cd/E17076_05/html/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Softmotions

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2019

2013

2012

1994

Current release

4.1.0, June 2022

18.1.40, May 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

GPLv2

Open Source

commercial license available

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

C++

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

hosted

Linux

server-less

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL interfaced based on SQLite is available

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JDBC
ODBC

in-process shared library

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

All languages supporting JDBC/ODBC

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

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

selectable replication factor

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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 and roles

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

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