DBMS > Badger vs. Bangdb vs. Microsoft Azure Data Explorer vs. Quasardb

System Properties Comparison Badger vs. Bangdb vs. Microsoft Azure Data Explorer vs. Quasardb

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

Fully managed big data interactive analytics platform

Distributed, high-performance timeseries database

Primary database model

Key-value store

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

column oriented

Time Series DBMS

Secondary database models

Spatial 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	0.14
Rank	#331	Overall
	#49	Key-value stores

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

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

github.com/dgraph-io/badger

bangdb.com

azure.microsoft.com/services/data-explorer

quasar.ai

Technical documentation

godoc.org/github.com/dgraph-io/badger

docs.bangdb.com

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

doc.quasar.ai/master

Developer

DGraph Labs

Sachin Sinha, BangDB

Microsoft

quasardb

Initial release

2017

2012

2019

2009

Current release

BangDB 2.0, October 2021

cloud service with continuous releases

3.14.1, January 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD 3

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

hosted

BSD
Linux
OS X
Windows

Data scheme

schema-free

Fixed schema with schema-less datatypes (dynamic)

schema-free

Typing

predefined data types such as float or date

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

yes

integer and binary

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.

yes

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

all fields are automatically indexed

yes

with tags

SQL

Support of SQL

SQL like support with command line tool

Kusto Query Language (KQL), SQL subset

SQL-like query language

APIs and other access methods

Proprietary protocol
RESTful HTTP API

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

HTTP API

Supported programming languages

C
C#
C++
Java
Python

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

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

Triggers

yes, Notifications (with Streaming only)

yes

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

Partitioning methods

Methods for storing different data on different nodes

none

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

Sharding

Implicit feature of the cloud service

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

yes

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

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

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

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Tunable consistency, set CAP knob accordingly

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

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

by using LevelDB

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

Transient mode

User concepts

Access control

yes (enterprise version only)

Azure Active Directory Authentication

Cryptographically strong user authentication and audit trail

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