DBMS > Bangdb vs. EsgynDB vs. Oracle Berkeley DB vs. YugabyteDB

System Properties Comparison Bangdb vs. EsgynDB vs. Oracle Berkeley DB vs. YugabyteDB

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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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Widely used in-process key-value store

High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Wide column store

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

Score	0.07
Rank	#346	Overall
	#47	Document stores
	#35	Graph DBMS
	#32	Time Series DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	1.88
Rank	#130	Overall
	#23	Key-value stores
	#3	Native XML DBMS

Score	2.48
Rank	#108	Overall
	#53	Relational DBMS

Website

bangdb.com

www.esgyn.cn

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

www.yugabyte.com

Technical documentation

docs.bangdb.com

docs.oracle.com/cd/E17076_05/html/index.html

docs.yugabyte.com
github.com/yugabyte/yugabyte-db

Developer

Sachin Sinha, BangDB

Esgyn

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Yugabyte Inc.

Initial release

2012

2015

1994

2017

Current release

BangDB 2.0, October 2021

18.1.40, May 2020

2.19, September 2023

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

commercial license available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.

Implementation language

C, C++

C++, Java

C, Java, C++ (depending on the Berkeley DB edition)

C and C++

Server operating systems

Linux

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
OS X

Data scheme

schema-free

yes

schema-free

depending on used data model

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

only with the Berkeley DB XML edition

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

SQL interfaced based on SQLite is available

yes, PostgreSQL compatible

APIs and other access methods

Proprietary protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC

JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL

Supported programming languages

C
C#
C++
Java
Python

All languages supporting JDBC/ODBC/ADO.Net

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

yes

sql, plpgsql, C

Triggers

yes, Notifications (with Streaming only)

yes

only for the SQL API

yes

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

Sharding

none

Hash and Range Sharding, row-level geo-partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication between multi datacenters

Source-replica replication

Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability

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

Strong consistency on writes and tunable consistency on reads

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.

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

based on RocksDB

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

yes

More information provided by the system vendor

Specific characteristics

YugabyteDB is an open source distributed SQL database for cloud native transactional...
» more

Competitive advantages

PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
» more

Typical application scenarios

Systems of record and engagement for cloud native applications that require resilience,...
» more

Market metrics

2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
» more

Licensing and pricing models

Apache 2.0 license for the database
» more

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