DBMS > Alibaba Cloud Table Store vs. Ehcache vs. Elasticsearch vs. HugeGraph vs. Snowflake

System Properties Comparison Alibaba Cloud Table Store vs. Ehcache vs. Elasticsearch vs. HugeGraph vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

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

A fast-speed and highly-scalable Graph DBMS

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.alibabacloud.com/product/table-store

www.ehcache.org

www.elastic.co/elasticsearch

github.com/hugegraph
hugegraph.apache.org

www.snowflake.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

www.ehcache.org/documentation

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

hugegraph.apache.org/docs

docs.snowflake.net/manuals/index.html

Developer

Alibaba

Terracotta Inc, owned by Software AG

Elastic

Baidu

Snowflake Computing Inc.

Initial release

2016

2009

2010

2018

2014

Current release

3.10.0, March 2022

8.6, January 2023

0.9

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

Open Source

Elastic License

Open Source

Apache Version 2.0

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

Server operating systems

hosted

All OS with a Java VM

Linux
macOS
Unix

hosted

Data scheme

schema-free

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

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

yes

Secondary indexes

yes

All search fields are automatically indexed

yes

also supports composite index and range index

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

HTTP API

JCache

Java API
RESTful HTTP/JSON API

Java API
RESTful HTTP API
TinkerPop Gremlin

CLI Client
JDBC
ODBC

Supported programming languages

Java
Python

Java

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

Groovy
Java
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

asynchronous Gremlin script jobs

user defined functions

Triggers

yes

Cache Event Listeners

yes

by using the 'percolation' feature

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

by using Terracotta Server

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

by using Terracotta Server

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

via hugegraph-spark

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

edges in graph

yes

Transaction concepts

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

Atomic single-row operations

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 based on subaccounts and tokens

Users, roles and permissions

Users with fine-grained authorization concept, user roles and pluggable authentication

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