DBMS > Alibaba Cloud Table Store vs. Blazegraph vs. Elasticsearch vs. Microsoft Azure Synapse Analytics vs. Snowflake

System Properties Comparison Alibaba Cloud Table Store vs. Blazegraph vs. Elasticsearch vs. Microsoft Azure Synapse Analytics vs. Snowflake

Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Description

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

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

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

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

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	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	0.81
Rank	#213	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.alibabacloud.com/product/table-store

blazegraph.com

www.elastic.co/elasticsearch

azure.microsoft.com/services/synapse-analytics

www.snowflake.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

wiki.blazegraph.com

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

docs.microsoft.com/azure/synapse-analytics

docs.snowflake.net/manuals/index.html

Developer

Alibaba

Blazegraph

Elastic

Microsoft

Snowflake Computing Inc.

Initial release

2016

2006

2010

2016

2014

Current release

2.1.5, March 2019

8.6, January 2023

License

Commercial or Open Source

commercial

Open Source

extended commercial license available

Open Source

Elastic License

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

hosted

Linux
OS X
Windows

All OS with a Java VM

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

RDF literal 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

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SPARQL is used as query language

SQL-like query language

yes

APIs and other access methods

HTTP API

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

Java
Python

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

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

C#
Java
PHP

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Transact SQL

user defined functions

Triggers

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

Sharding, horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

Transaction concepts

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

Atomic single-row operations

ACID

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.

Memcached and Redis integration

User concepts

Access control

Access rights based on subaccounts and tokens

Security and Authentication via Web Application Container (Tomcat, Jetty)

yes

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

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