DBMS > AllegroGraph vs. Apache Drill vs. Brytlyt vs. SQLite vs. Trafodion

System Properties Comparison AllegroGraph vs. Apache Drill vs. Brytlyt vs. SQLite vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

High performance, persistent RDF store with additional support for Graph DBMS

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

Widely used embeddable, in-process RDBMS

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Document store
Relational DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.13
Rank	#179	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

Technical documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

drill.apache.org/docs

docs.brytlyt.io

www.sqlite.org/docs.html

trafodion.apache.org/documentation.html

Developer

Franz Inc.

Apache Software Foundation

Brytlyt

Dwayne Richard Hipp

Apache Software Foundation, originally developed by HP

Initial release

2004

2012

2016

2000

2014

Current release

8.0, December 2023

1.20.3, January 2023

5.0, August 2023

3.46.0 (23 May 2024), May 2024

2.3.0, February 2019

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

Apache Version 2

commercial

Open Source

Public Domain

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.

Implementation language

C, C++ and CUDA

C++, Java

Server operating systems

Linux
OS X
Windows

server-less

Linux

Data scheme

yes

RDF schemas

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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.

bulk load of XML files possible

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

SQL SELECT statement is SQL:2003 compliant

yes

SQL-92 is not fully supported

yes

APIs and other access methods

RESTful HTTP API
SPARQL

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
ODBC

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

C++

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

user defined functions

in PL/pgSQL

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

none

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

yes

User concepts

Access control

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

Depending on the underlying data source

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more

Competitive advantages

AllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more

News

How a Neuro-Symbolic AI Approach Can Improve Trust in AI Apps
23 May 2024

Can Neuro-Symbolic AI Solve AI’s Weaknesses?
17 April 2024

100 Companies That Matter in KM – Franz Inc.
3 April 2024

Exploring AllegroGraph v8 – Unleashing the Power of Neuro-Symbolic AI (Recorded Webinar)
9 February 2024

What is Neuro-Symbolic AI?
23 January 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.