DBMS > Ehcache vs. Heroic vs. Microsoft Azure Data Explorer vs. SWC-DB vs. Teradata Aster

System Properties Comparison Ehcache vs. Heroic vs. Microsoft Azure Data Explorer vs. SWC-DB vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

A widely adopted Java cache with tiered storage options

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Fully managed big data interactive analytics platform

A high performance, scalable Wide Column DBMS

Platform for big data analytics on multistructured data sources and types

Primary database model

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

Time Series DBMS

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

Score	4.79
Rank	#66	Overall
	#8	Key-value stores

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	3.28
Rank	#83	Overall
	#45	Relational DBMS

Score	0.01
Rank	#378	Overall
	#13	Wide column stores

Website

www.ehcache.org

github.com/spotify/heroic

azure.microsoft.com/services/data-explorer

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

www.ehcache.org/documentation

spotify.github.io/heroic

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

Developer

Terracotta Inc, owned by Software AG

Spotify

Microsoft

Alex Kashirin

Teradata

Initial release

2009

2014

2019

2020

2005

Current release

3.10.0, March 2022

cloud service with continuous releases

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 2.0

commercial

Open Source

GPL V3

commercial

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

Java

C++

Server operating systems

All OS with a Java VM

hosted

Linux

Data scheme

schema-free

Fixed schema with schema-less datatypes (dynamic)

schema-free

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

yes

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

in Aster File Store

Secondary indexes

yes

via Elasticsearch

all fields are automatically indexed

yes

SQL

Support of SQL

Kusto Query Language (KQL), SQL subset

SQL-like query language

yes

APIs and other access methods

JCache

HQL (Heroic Query Language, a JSON-based language)
HTTP API

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

Proprietary protocol
Thrift

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

Java

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

C++

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

R packages

Triggers

yes

Cache Event Listeners

yes

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

yes

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

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Eventual Consistency
Immediate Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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

Azure Active Directory Authentication

fine grained access rights according to SQL-standard

More information provided by the system vendor

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Jira Data Center user? Here's a critical Ehcache vulnerability to spoil your day
22 July 2021, The Register

Atlassian asks customers to patch critical Jira vulnerability
22 July 2021, BleepingComputer

Critical Jira Flaw in Atlassian Could Lead to RCE
22 July 2021, Threatpost

How to partition Sonatype Nexus Repository: Targets, privileges, and roles
9 February 2010, Sonatype Blog

Implementing fallback with cached data
8 October 2018, O'Reilly Media

provided by Google News

We’re retiring Azure Time Series Insights on 7 July 2024 – transition to Azure Data Explorer
31 May 2024, azure.microsoft.com

Update records in a Kusto Database (public preview)
20 February 2024, azure.microsoft.com

Announcing General Availability to migrate Virtual Network injected Azure Data Explorer Cluster to Private Endpoints
5 February 2024, azure.microsoft.com

Announcing General Availability of Graph Semantics in Kusto
27 May 2024, azure.microsoft.com

General availability: Azure Data Explorer adds new geospatial capabilities
23 January 2024, azure.microsoft.com

provided by Google News

2022 All O-Zone Football Team
17 December 2022, Ozarks Sports Zone

provided by Google News

Case study: Siemens reduces train failures with Teradata Aster
12 September 2016, RCR Wireless News

Teradata's Aster shows how the flowers of fraud bloom
23 April 2015, The Register

Teradata Integrates Big Data Analytic Architecture
22 October 2012, PR Newswire

An American Dream Story, With A Silicon Valley Twist
14 August 2013, Forbes

Gartner, IBM, Teradata make Big Data announcements
17 October 2012, ZDNet

provided by Google News

Share this page