DBMS > Amazon DocumentDB vs. EJDB vs. Hypertable vs. InfluxDB vs. Oracle

System Properties Comparison Amazon DocumentDB vs. EJDB vs. Hypertable vs. InfluxDB vs. Oracle

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

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

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

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

DBMS for storing time series, events and metrics

Widely used RDBMS

Primary database model

Secondary database models

Spatial DBMS

with GEO package

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph

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

Score	1.78
Rank	#130	Overall
	#24	Document stores

Score	0.10
Rank	#322	Overall
	#44	Document stores

Score	29.78
Rank	#29	Overall
	#1	Time Series DBMS

Score	1260.80
Rank	#1	Overall
	#1	Relational DBMS

Website

aws.amazon.com/documentdb

ejdb.org

www.influxdata.com/products/influxdb-overview

www.oracle.com/database

Technical documentation

aws.amazon.com/documentdb/resources

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

docs.influxdata.com/influxdb

docs.oracle.com/en/database

Developer

Softmotions

Hypertable Inc.

Oracle

Initial release

2019

2012

2009

2013

1980

Current release

0.9.8.11, March 2016

2.3, June 2022

19c, February 2019

License

Commercial or Open Source

commercial

Open Source

GPLv2

Open Source

GNU version 3. Commercial license available

Open Source

MIT-License; commercial enterprise version available

commercial

restricted free version is 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 and C++

Server operating systems

hosted

server-less

Linux
OS X
Windows

an inofficial Windows port is available

Linux
OS X

through Homebrew

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

Numeric data and Strings

yes

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

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

in-process shared library

C++ API
Thrift

HTTP API
JSON over UDP

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

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

C++
Java
Perl
PHP
Python
Ruby

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

in enterprise version only

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

selectable replication factor on file system level

selectable replication factor

in enterprise version only

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

Atomic single-document operations

ACID

isolation level can be parameterized

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

Depending on used storage engine

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

Access rights for users and roles

simple rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

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