DBMS > Amazon Aurora vs. Bangdb vs. RocksDB vs. Splunk vs. Trafodion

System Properties Comparison Amazon Aurora vs. Bangdb vs. RocksDB vs. Splunk vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

MySQL and PostgreSQL compatible cloud service by Amazon

Converged and high performance database for device data, events, time series, document and graph

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Analytics Platform for Big Data

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Document store
Graph DBMS
Time Series DBMS

Key-value store

Search engine

Relational DBMS

Secondary database models

Document store

Spatial DBMS

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

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

aws.amazon.com/rds/aurora

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

docs.bangdb.com

github.com/facebook/rocksdb/wiki

docs.splunk.com/Documentation/Splunk

trafodion.apache.org/documentation.html

Developer

Amazon

Sachin Sinha, BangDB

Facebook, Inc.

Splunk Inc.

Apache Software Foundation, originally developed by HP

Initial release

2015

2012

2013

2003

2014

Current release

BangDB 2.0, October 2021

8.11.4, April 2024

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

BSD 3

Open Source

BSD

commercial

Limited free edition and free developer edition available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

C++

C++, Java

Server operating systems

hosted

Linux

Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

yes

SQL like support with command line tool

Splunk Search Processing Language for search commands

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

Proprietary protocol
RESTful HTTP API

C++ API
Java API

HTTP REST

ADO.NET
JDBC
ODBC

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C#
C++
Java
Python

C
C++
Go
Java
Perl
Python
Ruby

C#
Java
JavaScript
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

Java Stored Procedures

Triggers

yes

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor, Knob for CAP (enterprise version only)

yes

Multi-source replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

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

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

yes, run db with in-memory only mode

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes (enterprise version only)

Access rights for users and roles

fine grained access rights according to SQL-standard

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