DBMS > Apache Druid vs. Cassandra vs. Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. SwayDB

System Properties Comparison Apache Druid vs. Cassandra vs. Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

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

Relational DBMS
Time Series DBMS

Wide column store

Key-value store
Wide column store

Relational DBMS

column oriented

Key-value store

Secondary database models

Vector DBMS

starting with release V5

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	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	98.83
Rank	#12	Overall
	#1	Wide column stores

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

druid.apache.org

cassandra.apache.org

cloud.google.com/bigtable

azure.microsoft.com/services/data-explorer

swaydb.simer.au

Technical documentation

druid.apache.org/docs/latest/design

cassandra.apache.org/doc/latest

cloud.google.com/bigtable/docs

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

Developer

Apache Software Foundation and contributors

Apache Software Foundation

Apache top level project, originally developped by Facebook

Google

Microsoft

Simer Plaha

Initial release

2012

2008

2015

2019

2018

Current release

29.0.1, April 2024

4.1.3, July 2023

cloud service with continuous releases

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache version 2

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

Scala

Server operating systems

Linux
OS X
Unix

BSD
Linux
OS X
Windows

hosted

Data scheme

yes

schema-less columns are supported

schema-free

Fixed schema with schema-less datatypes (dynamic)

schema-free

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

restricted

only equality queries, not always the best performing solution

all fields are automatically indexed

SQL

Support of SQL

SQL for querying

SQL-like SELECT, DML and DDL statements (CQL)

Kusto Query Language (KQL), SQL subset

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

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

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

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

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

Java
Kotlin
Scala

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

Triggers

yes

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

no "single point of failure"

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

selectable replication factor

Representation of geographical distribution of servers is possible

Internal replication in Colossus, and regional replication between two clusters in different zones

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

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomicity and isolation are supported for single operations

Atomic single-row operations

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights for users can be defined per object

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Azure Active Directory Authentication

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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Market metrics

Cassandra is used by 40% of the Fortune 100.
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Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
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