DBMS > Amazon DocumentDB vs. BigchainDB vs. ReductStore vs. Splunk vs. TimesTen

System Properties Comparison Amazon DocumentDB vs. BigchainDB vs. ReductStore vs. Splunk vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

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

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Analytics Platform for Big Data

In-Memory RDBMS compatible to Oracle

Primary database model

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

aws.amazon.com/documentdb

www.bigchaindb.com

github.com/reductstore
www.reduct.store

www.splunk.com

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

Technical documentation

aws.amazon.com/documentdb/resources

bigchaindb.readthedocs.io/en/latest

www.reduct.store/docs

docs.splunk.com/Documentation/Splunk

docs.oracle.com/database/timesten-18.1

Developer

ReductStore LLC

Splunk Inc.

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2019

2016

2023

2003

1998

Current release

1.9, March 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

AGPL v3

Open Source

Business Source License 1.1

commercial

Limited free edition and free developer edition available

commercial

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

Python

C++, Rust

Server operating systems

hosted

Linux

Docker
Linux
macOS
Windows

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

Splunk Search Processing Language for search commands

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

CLI Client
RESTful HTTP API

HTTP API

HTTP REST

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Go
Haskell
Java
JavaScript
Python
Ruby

C++
JavaScript (Node.js)
Python
Rust

C#
Java
JavaScript
PHP
Python
Ruby

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

PL/SQL

Triggers

yes

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

Multi-source replication

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

yes

by means of logfiles and checkpoints

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

yes

Access rights for users and roles

fine grained access rights according to SQL-standard

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More resources

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