DBMS > Interbase vs. Titan vs. WakandaDB vs. XTDB

System Properties Comparison Interbase vs. Titan vs. WakandaDB vs. XTDB

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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

Light-weight proven RDBMS

originally from Borland

Titan is a Graph DBMS optimized for distributed clusters.

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

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

Score	4.08
Rank	#75	Overall
	#41	Relational DBMS

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.embarcadero.com/products/interbase

github.com/thinkaurelius/titan

wakanda.github.io

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.embarcadero.com/products/interbase

github.com/thinkaurelius/titan/wiki

wakanda.github.io/doc

www.xtdb.com/docs

Developer

Embarcadero

Aurelius, owned by DataStax

Wakanda SAS

Juxt Ltd.

Initial release

1984

2012

2019

Current release

InterBase 2020, December 2019

2.7.0 (April 29, 2019), April 2019

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Apache license, version 2.0

Open Source

AGPLv3, extended commercial license available

Open Source

MIT License

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.

Implementation language

Java

C++, JavaScript

Clojure

Server operating systems

Android
iOS
Linux
OS X
Windows

Linux
OS X
Unix
Windows

Linux
OS X
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

limited SQL, making use of Apache Calcite

APIs and other access methods

ADO.NET
JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

RESTful HTTP API

HTTP REST
JDBC

Supported programming languages

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

Clojure
Java
Python

JavaScript

Clojure
Java

Server-side scripts

Stored procedures

yes

Interbase procedure and trigger language

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

via pluggable storage backends

none

Replication methods

Methods for redundantly storing data on multiple nodes

Interbase Change Views

yes

none

yes, each node contains all data

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

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

Multiversion concurreny control

yes

Durability

Support for making data persistent

yes

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

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

User authentification and security via Rexster Graph Server

yes

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More resources

DB-Engines blog posts

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

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