DBMS > Amazon DynamoDB vs. EXASOL vs. IRONdb vs. Microsoft Azure Data Explorer vs. SwayDB

System Properties Comparison Amazon DynamoDB vs. EXASOL vs. IRONdb vs. Microsoft Azure Data Explorer vs. SwayDB

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

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
Key-value store

column oriented

Secondary database models

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	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

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

Website

aws.amazon.com/dynamodb

www.exasol.com

www.circonus.com/solutions/time-series-database/

azure.microsoft.com/services/data-explorer

swaydb.simer.au

Technical documentation

docs.aws.amazon.com/dynamodb

www.exasol.com/resources

docs.circonus.com/irondb/category/getting-started

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

Developer

Amazon

Exasol

Circonus LLC.

Microsoft

Simer Plaha

Initial release

2012

2000

2017

2019

2018

Current release

V0.10.20, January 2018

cloud service with continuous releases

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

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 and C++

Scala

Server operating systems

hosted

Linux

hosted

Data scheme

schema-free

yes

schema-free

Fixed schema with schema-less datatypes (dynamic)

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

all fields are automatically indexed

SQL

Support of SQL

yes

SQL-like query language (Circonus Analytics Query Language: CAQL)

Kusto Query Language (KQL), SQL subset

APIs and other access methods

RESTful HTTP API

.Net
JDBC
ODBC
WebSocket

HTTP API

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

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Java
Lua
Python
R

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

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

Java
Kotlin
Scala

Server-side scripts

Stored procedures

user defined functions

yes, in Lua

Yes, possible languages: KQL, Python, R

Triggers

yes

by integration with AWS Lambda

yes

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

configurable replication factor, datacenter aware

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

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Hadoop integration

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

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access rights for users, groups and roles according to SQL-standard

Azure Active Directory Authentication

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