DBMS > Bangdb vs. Derby vs. Google Cloud Bigtable vs. Oracle Coherence

System Properties Comparison Bangdb vs. Derby vs. Google Cloud Bigtable vs. Oracle Coherence

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Editorial information provided by DB-Engines

Name

Description

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Oracles in-memory data grid solution

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Key-value store
Wide column store

Key-value store

Secondary database models

Spatial DBMS

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

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

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Website

bangdb.com

db.apache.org/derby

cloud.google.com/bigtable

www.oracle.com/java/coherence

Technical documentation

docs.bangdb.com

db.apache.org/derby/manuals/index.html

cloud.google.com/bigtable/docs

docs.oracle.com/en/middleware/standalone/coherence

Developer

Sachin Sinha, BangDB

Apache Software Foundation

Google

Oracle

Initial release

2012

1997

2015

2007

Current release

BangDB 2.0, October 2021

10.17.1.0, November 2023

14.1, August 2023

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache version 2

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++

Java

Server operating systems

Linux

All OS with a Java VM

hosted

All OS with a Java VM

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

SQL like support with command line tool

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

JCache
JPA
RESTful HTTP API

Supported programming languages

C
C#
C++
Java
Python

Java

C#
C++
Go
Java
JavaScript (Node.js)
Python

.Net
C++
Java

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes, Notifications (with Streaming only)

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

Internal replication in Colossus, and regional replication between two clusters in different zones

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-row operations

configurable

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

optionally

In-memory capabilities

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

yes, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

fine grained access rights according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

authentification to access the cache via certificates or http basic authentication

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