DBMS > Amazon DocumentDB vs. FatDB vs. InfluxDB vs. Oracle vs. TerarkDB

System Properties Comparison Amazon DocumentDB vs. FatDB vs. InfluxDB vs. Oracle vs. TerarkDB

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

DBMS for storing time series, events and metrics

Widely used RDBMS

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Document store

Document store
Key-value store

Time Series DBMS

Relational DBMS

Key-value store

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
Vector DBMS

since Oracle 23

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

aws.amazon.com/documentdb

www.influxdata.com/products/influxdb-overview

www.oracle.com/database

github.com/bytedance/terarkdb

Technical documentation

aws.amazon.com/documentdb/resources

docs.influxdata.com/influxdb

docs.oracle.com/en/database

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

FatCloud

Oracle

ByteDance, originally Terark

Initial release

2019

2012

2013

1980

2016

Current release

2.7.6, April 2024

23c, September 2023

License

Commercial or Open Source

commercial

Open Source

MIT-License; commercial enterprise version available

commercial

restricted free version is available

commercial

restricted open source version 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 and C++

C++

Server operating systems

hosted

Windows

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

schema-free

Typing

predefined data types such as float or date

yes

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

SQL

Support of SQL

Via inetgration in SQL Server

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

HTTP API
JSON over UDP

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

C++ API
Java API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

.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

C++
Java

Server-side scripts

Stored procedures

yes

via applications

PL/SQL

also stored procedures in Java possible

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

in enterprise version only

Sharding, horizontal partitioning

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

in enterprise version only

Multi-source replication
Source-replica replication

none

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

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef 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

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'

yes

User concepts

Access control

Access rights for users and roles

Can implement custom security layer via applications

simple rights management via user accounts

fine grained access rights according to SQL-standard

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