DBMS > EsgynDB vs. Google Cloud Bigtable vs. HyperSQL vs. Interbase

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. HyperSQL vs. Interbase

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Editorial information provided by DB-Engines

Name

Description

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

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Light-weight proven RDBMS

originally from Borland

Primary database model

Relational DBMS

Key-value store
Wide column store

Relational DBMS

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

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

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	4.61
Rank	#72	Overall
	#39	Relational DBMS

Website

www.esgyn.cn

cloud.google.com/bigtable

hsqldb.org

www.embarcadero.com/products/interbase

Technical documentation

cloud.google.com/bigtable/docs

hsqldb.org/web/hsqlDocsFrame.html

docs.embarcadero.com/products/interbase

Developer

Esgyn

Google

Embarcadero

Initial release

2015

2001

1984

Current release

2.7.2, June 2023

InterBase 2020, December 2019

License

Commercial or Open Source

commercial

Open Source

based on BSD license

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++, Java

Java

Server operating systems

Linux

hosted

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Android
iOS
Linux
OS X
Windows

Data scheme

yes

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.

export as XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

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

HTTP API

JDBC via HTTP
JDBC
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

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

All languages supporting JDBC/ODBC
Java

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

Java, SQL

yes

Interbase procedure and trigger language

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

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

none

Interbase Change Views

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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

fine grained access rights according to SQL-standard

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