DBMS > Alibaba Cloud MaxCompute vs. Ehcache vs. Elasticsearch vs. Hive vs. SAP HANA

System Properties Comparison Alibaba Cloud MaxCompute vs. Ehcache vs. Elasticsearch vs. Hive vs. SAP HANA

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

A widely adopted Java cache with tiered storage options

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

data warehouse software for querying and managing large distributed datasets, built on Hadoop

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Relational DBMS

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

Key-value store

Search engine

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.84
Rank	#209	Overall
	#98	Relational DBMS

Score	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

www.ehcache.org

www.elastic.co/elasticsearch

hive.apache.org

www.sap.com/products/hana.html

Technical documentation

www.alibabacloud.com/help/en/maxcompute

www.ehcache.org/documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

cwiki.apache.org/confluence/display/Hive/Home

help.sap.com/hana

Developer

Alibaba

Terracotta Inc, owned by Software AG

Elastic

Apache Software Foundation

initially developed by Facebook

SAP

Initial release

2016

2009

2010

2012

2010

Current release

3.10.0, March 2022

8.6, January 2023

3.1.3, April 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

Open Source

Elastic License

Open Source

Apache Version 2

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

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

All OS with a Java VM

Appliance or cloud-service

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

JCache

Java API
RESTful HTTP/JSON API

JDBC
ODBC
Thrift

JDBC
ODBC

Supported programming languages

Java

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Java

yes

user defined functions and integration of map-reduce

SQLScript, R

Triggers

yes

Cache Event Listeners

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

by using Terracotta Server

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

by using Terracotta Server

yes

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

ES-Hadoop Connector

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable Consistency (Strong, Eventual, Weak)

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

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

Memcached and Redis integration

yes

User concepts

Access control

Access rights for users and roles

Access rights for users, groups and roles

yes

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