DBMS > Alibaba Cloud MaxCompute vs. Hawkular Metrics vs. Heroic vs. Splice Machine

System Properties Comparison Alibaba Cloud MaxCompute vs. Hawkular Metrics vs. Heroic vs. Splice Machine

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Editorial information provided by DB-Engines

Name

Description

MaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousing

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Relational DBMS

a graph-processing framework is available with the graphs being stored in tables

Time Series DBMS

Relational DBMS

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

Score	0.84
Rank	#209	Overall
	#98	Relational DBMS

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

www.hawkular.org

github.com/spotify/heroic

splicemachine.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

www.hawkular.org/hawkular-metrics/docs/user-guide

spotify.github.io/heroic

splicemachine.com/how-it-works

Developer

Alibaba

Community supported by Red Hat

Spotify

Splice Machine

Initial release

2016

2014

Current release

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

AGPL 3.0, commercial license available

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

Server operating systems

hosted

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

HTTP REST

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

JDBC
Native Spark Datasource
ODBC

Supported programming languages

Java

Go
Java
Python
Ruby

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

user defined functions

in Java

yes

Java

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

based on Cassandra

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

based on Cassandra

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

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

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