DBMS > Apache Drill vs. Apache Phoenix vs. Blazegraph vs. Elasticsearch vs. Microsoft Azure Synapse Analytics

System Properties Comparison Apache Drill vs. Apache Phoenix vs. Blazegraph vs. Elasticsearch vs. Microsoft Azure Synapse Analytics

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

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

A scale-out RDBMS with evolutionary schema built on Apache HBase

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

Primary database model

Document store
Relational DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	0.75
Rank	#219	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Website

drill.apache.org

phoenix.apache.org

blazegraph.com

www.elastic.co/elasticsearch

azure.microsoft.com/services/synapse-analytics

Technical documentation

drill.apache.org/docs

phoenix.apache.org

wiki.blazegraph.com

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

docs.microsoft.com/azure/synapse-analytics

Developer

Apache Software Foundation

Blazegraph

Elastic

Microsoft

Initial release

2012

2014

2006

2010

2016

Current release

1.20.3, January 2023

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

2.1.5, March 2019

8.6, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

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

Linux
OS X
Windows

Linux
Unix
Windows

Linux
OS X
Windows

All OS with a Java VM

hosted

Data scheme

schema-free

yes

late-bound, schema-on-read capabilities

schema-free

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

yes

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.

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

SPARQL is used as query language

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

Supported programming languages

C++

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

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

C#
Java
PHP

Server-side scripts

Stored procedures

user defined functions

yes

Transact SQL

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual 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

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

Memcached and Redis integration

User concepts

Access control

Depending on the underlying data source

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

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

yes

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