DBMS > EsgynDB vs. Ingres vs. Oracle Berkeley DB vs. Snowflake vs. Titan

System Properties Comparison EsgynDB vs. Ingres vs. Oracle Berkeley DB vs. Snowflake vs. Titan

Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

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

Well established RDBMS

Widely used in-process key-value store

Cloud-based data warehousing service for structured and semi-structured data

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

Graph DBMS

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.esgyn.cn

www.actian.com/databases/ingres

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

www.snowflake.com

github.com/thinkaurelius/titan

Technical documentation

docs.actian.com/ingres

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

docs.snowflake.net/manuals/index.html

github.com/thinkaurelius/titan/wiki

Developer

Esgyn

Actian Corporation

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Snowflake Computing Inc.

Aurelius, owned by DataStax

Initial release

2015

1974

originally developed at University Berkely in early 1970s

1994

2014

2012

Current release

11.2, May 2022

18.1.40, May 2020

License

Commercial or Open Source

commercial

Open Source

commercial license available

commercial

Open Source

Apache license, version 2.0

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

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

Java

Server operating systems

Linux

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

hosted

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

but tools for importing/exporting data from/to XML-files available

yes

only with the Berkeley DB XML edition

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

CLI Client
JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

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

JavaScript (Node.js)
Python

Clojure
Java
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

user defined functions

yes

Triggers

yes

only for the SQL API

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

none

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Ingres Replicator

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

Users with fine-grained authorization concept, user roles and pluggable authentication

User authentification and security via Rexster Graph Server

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