DBMS > Elasticsearch vs. Heroic vs. Microsoft SQL Server vs. OpenQM vs. Vertica

System Properties Comparison Elasticsearch vs. Heroic vs. Microsoft SQL Server vs. OpenQM vs. Vertica

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Microsofts flagship relational DBMS

QpenQM is a high-performance, self-tuning, multi-value DBMS

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Column oriented

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Document store
Graph DBMS
Spatial DBMS

Spatial DBMS
Time Series DBMS

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

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Website

www.elastic.co/elasticsearch

github.com/spotify/heroic

www.microsoft.com/en-us/sql-server

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.vertica.com

Technical documentation

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

spotify.github.io/heroic

learn.microsoft.com/en-US/sql/sql-server

vertica.com/documentation

Developer

Elastic

Spotify

Microsoft

Rocket Software, originally Martin Phillips

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2010

2014

1989

1993

2005

Current release

8.6, January 2023

SQL Server 2022, November 2022

3.4-12

12.0.3, January 2023

License

Commercial or Open Source

Open Source

Elastic License

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

GPLv2, extended commercial license available

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

All OS with a Java VM

Linux
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux

Data scheme

schema-free

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

schema-free

yes

with some exceptions

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

via Elasticsearch

yes

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

SQL-like query language

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

Java API
RESTful HTTP/JSON API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.Net
Basic
C
Java
Objective C
PHP
Python

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

by using the 'percolation' feature

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

yes

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, but depending on the SQL-Server Edition

yes

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Bi-directional Spark integration

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

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

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

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; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

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Licensing and pricing models

Cost-based models and subscription-based models are both available. One license is...
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