DBMS > Amazon Redshift vs. Bangdb vs. LevelDB vs. TimesTen vs. UniData,UniVerse

System Properties Comparison Amazon Redshift vs. Bangdb vs. LevelDB vs. TimesTen vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

In-Memory RDBMS compatible to Oracle

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Relational DBMS

Document store
Graph DBMS
Time Series DBMS

Key-value store

Relational DBMS

Multivalue DBMS

Secondary database models

Spatial DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

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

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Website

aws.amazon.com/redshift

bangdb.com

github.com/google/leveldb

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

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

docs.aws.amazon.com/redshift

docs.bangdb.com

github.com/google/leveldb/blob/main/doc/index.md

docs.oracle.com/database/timesten-18.1

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Amazon (based on PostgreSQL)

Sachin Sinha, BangDB

Google

Oracle, TimesTen Performance Software, HP

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

Rocket Software

Initial release

2012

2011

1998

1985

Current release

BangDB 2.0, October 2021

1.23, February 2021

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

BSD 3

Open Source

BSD

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

C, C++

C++

Server operating systems

hosted

Linux

Illumos
Linux
OS X
Windows

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

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

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

yes

optional

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.

Secondary indexes

restricted

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL like support with command line tool

yes

APIs and other access methods

JDBC
ODBC

Proprietary protocol
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Java
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C++
Java
PL/SQL

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

user defined functions

in Python

PL/SQL

yes

Triggers

yes, Notifications (with Streaming only)

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

none

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

configurable

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

with automatic compression on writes

yes

by means of logfiles and checkpoints

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)

fine grained access rights according to SQL-standard

Access rights according to SQL-standard and operating system based

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