DBMS > AllegroGraph vs. Bangdb vs. HarperDB vs. SwayDB

System Properties Comparison AllegroGraph vs. Bangdb vs. HarperDB vs. SwayDB

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Editorial information provided by DB-Engines

Name

Description

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

Converged and high performance database for device data, events, time series, document and graph

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Document store
Graph DBMS
Time Series DBMS

Document store

Key-value store

Secondary database models

Spatial DBMS

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

Score	1.06
Rank	#187	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

Technical documentation

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

docs.bangdb.com

docs.harperdb.io/docs

Developer

Franz Inc.

Sachin Sinha, BangDB

HarperDB

Simer Plaha

Initial release

2004

2012

2017

2018

Current release

8.0, December 2023

BangDB 2.0, October 2021

3.1, August 2021

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

BSD 3

commercial

free community edition available

Open Source

GNU Affero GPL V3.0

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++

Node.js

Scala

Server operating systems

Linux
OS X
Windows

Linux

Linux
OS X

Data scheme

yes

RDF schemas

schema-free

dynamic schema

schema-free

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

yes

JSON data types

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

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SPARQL is used as query language

SQL like support with command line tool

SQL-like data manipulation statements

APIs and other access methods

RESTful HTTP API
SPARQL

Proprietary protocol
RESTful HTTP API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

C
C#
C++
Java
Python

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

Custom Functions

since release 3.1

Triggers

yes

yes, Notifications (with Streaming only)

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

A table resides as a whole on one (or more) nodes in a cluster

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

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

yes

the nodes on which a table resides can be defined

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Atomic execution of specific operations

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes, using LMDB

yes

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

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

yes (enterprise version only)

Access rights for users and roles

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

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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

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