DBMS > Elasticsearch vs. HEAVY.AI vs. Kinetica vs. SAP SQL Anywhere vs. Snowflake

System Properties Comparison Elasticsearch vs. HEAVY.AI vs. Kinetica vs. SAP SQL Anywhere vs. Snowflake

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

Fully vectorized database across both GPUs and CPUs

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

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

Primary database model

Search engine

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Vector 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	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.elastic.co/elasticsearch

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

www.kinetica.com

www.sap.com/products/technology-platform/sql-anywhere.html

www.snowflake.com

Technical documentation

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

docs.heavy.ai

docs.kinetica.com

help.sap.com/docs/SAP_SQL_Anywhere

docs.snowflake.net/manuals/index.html

Developer

Elastic

HEAVY.AI, Inc.

Kinetica

SAP

formerly Sybase

Snowflake Computing Inc.

Initial release

2010

2016

2012

1992

2014

Current release

8.6, January 2023

5.10, January 2022

7.1, August 2021

17, July 2015

License

Commercial or Open Source

Open Source

Elastic License

Open Source

Apache Version 2; enterprise edition available

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++ and CUDA

C, C++

Server operating systems

All OS with a Java VM

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

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

SQL

Support of SQL

SQL-like query language

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

Java API
RESTful HTTP/JSON API

JDBC
ODBC
Thrift
Vega

JDBC
ODBC
RESTful HTTP API

ADO.NET
HTTP API
JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

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

All languages supporting JDBC/ODBC/Thrift
Python

C++
Java
JavaScript (Node.js)
Python

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

yes, in C/C++, Java, .Net or Perl

user defined functions

Triggers

yes

by using the 'percolation' feature

yes

triggers when inserted values for one or more columns fall within a specified range

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

Source-replica replication

Database mirroring

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

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

Immediate Consistency or Eventual Consistency depending on configuration

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

GPU vRAM or System RAM

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

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

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