DBMS > Elasticsearch vs. HEAVY.AI vs. Microsoft Azure Cosmos DB vs. Postgres-XL vs. SpatiaLite

System Properties Comparison Elasticsearch vs. HEAVY.AI vs. Microsoft Azure Cosmos DB vs. Postgres-XL vs. SpatiaLite

Editorial information provided by DB-Engines

Name

Description

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 high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Globally distributed, horizontally scalable, multi-model database service

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Spatial extension of SQLite

Primary database model

Search engine

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Spatial DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Spatial DBMS

Document store
Spatial DBMS

Relational DBMS

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

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

www.elastic.co/elasticsearch

github.com/heavyai/heavydb
www.heavy.ai

azure.microsoft.com/services/cosmos-db

www.postgres-xl.org

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

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

docs.heavy.ai

learn.microsoft.com/azure/cosmos-db

www.postgres-xl.org/documentation

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Elastic

HEAVY.AI, Inc.

Microsoft

Alessandro Furieri

Initial release

2010

2016

2014

since 2012, originally named StormDB

2008

Current release

8.6, January 2023

5.10, January 2022

10 R1, October 2018

5.0.0, August 2020

License

Commercial or Open Source

Open Source

Elastic License

Open Source

Apache Version 2; enterprise edition available

commercial

Open Source

Mozilla public license

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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++ and CUDA

C++

Server operating systems

All OS with a Java VM

Linux

hosted

Linux
macOS

server-less

Data scheme

schema-free

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

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON 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

XML type, but no XML query functionality

Secondary indexes

yes

All search fields are automatically indexed

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language

yes

distributed, parallel query execution

yes

APIs and other access methods

Java API
RESTful HTTP/JSON API

JDBC
ODBC
Thrift
Vega

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

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

All languages supporting JDBC/ODBC/Thrift
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

JavaScript

user defined functions

Triggers

yes

by using the 'percolation' feature

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

Implicit feature of the cloud service

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

MVCC

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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