DBMS > AllegroGraph vs. Bangdb vs. Couchbase vs. Microsoft Azure Data Explorer vs. SwayDB

System Properties Comparison AllegroGraph vs. Bangdb vs. Couchbase vs. Microsoft Azure Data Explorer vs. SwayDB

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

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Fully managed big data interactive analytics platform

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

Relational DBMS

column oriented

Key-value store

Secondary database models

Spatial DBMS

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

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	17.30
Rank	#36	Overall
	#5	Document stores

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

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

Website

allegrograph.com

bangdb.com

www.couchbase.com

azure.microsoft.com/services/data-explorer

swaydb.simer.au

Technical documentation

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

docs.bangdb.com

docs.couchbase.com

docs.microsoft.com/en-us/azure/data-explorer

Developer

Franz Inc.

Sachin Sinha, BangDB

Couchbase, Inc.

Microsoft

Simer Plaha

Initial release

2004

2012

2011

2019

2018

Current release

8.0, December 2023

BangDB 2.0, October 2021

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

cloud service with continuous releases

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

BSD 3

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

commercial

Open Source

GNU Affero GPL V3.0

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, C++

C, C++, Go and Erlang

Scala

Server operating systems

Linux
OS X
Windows

Linux

Linux
OS X
Windows

hosted

Data scheme

yes

RDF schemas

schema-free

Fixed schema with schema-less datatypes (dynamic)

schema-free

Typing

predefined data types such as float or date

yes

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

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-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

yes

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

all fields are automatically indexed

SQL

Support of SQL

SPARQL is used as query language

SQL like support with command line tool

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

Kusto Query Language (KQL), SQL subset

APIs and other access methods

RESTful HTTP API
SPARQL

Proprietary protocol
RESTful HTTP API

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

C
C#
C++
Java
Python

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

Yes, possible languages: KQL, Python, R

Triggers

yes

yes, Notifications (with Streaming only)

yes

via the TAP protocol

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

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

Automatic Sharding

Sharding

Implicit feature of the cloud service

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)

Multi-source replication

including cross data center replication
Source-replica replication

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Spark connector (open source): github.com/Azure/azure-kusto-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Tunable consistency, set CAP knob accordingly

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

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

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

Ephemeral buckets

yes

User concepts

Access control

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

yes (enterprise version only)

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Azure Active Directory Authentication

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

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

Allegro CL v11 – Now Available! – The Neuro-Symbolic AI Programming Platform
8 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.