DBMS > HEAVY.AI vs. PouchDB vs. Snowflake vs. Splunk vs. TerminusDB

System Properties Comparison HEAVY.AI vs. PouchDB vs. Snowflake vs. Splunk vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

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

JavaScript DBMS with an API inspired by CouchDB

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

Analytics Platform for Big Data

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Secondary database models

Spatial DBMS

Document store
RDF store

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

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

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

Technical documentation

docs.heavy.ai

pouchdb.com/guides

docs.snowflake.net/manuals/index.html

docs.splunk.com/Documentation/Splunk

terminusdb.github.io/terminusdb/#

Developer

HEAVY.AI, Inc.

Apache Software Foundation

Snowflake Computing Inc.

Splunk Inc.

DataChemist Ltd.

Initial release

2016

2012

2014

2003

2018

Current release

5.10, January 2022

7.1.1, June 2019

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

Open Source

commercial

Limited free edition and free developer edition available

Open Source

GPL V3

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

C++ and CUDA

JavaScript

Prolog, Rust

Server operating systems

Linux

server-less, requires a JavaScript environment (browser, Node.js)

hosted

Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

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

via views

yes

SQL

Support of SQL

yes

Splunk Search Processing Language for search commands

SQL-like query language (WOQL)

APIs and other access methods

JDBC
ODBC
Thrift
Vega

HTTP REST

only for PouchDB Server
JavaScript API

CLI Client
JDBC
ODBC

HTTP REST

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

JavaScript (Node.js)
Python

C#
Java
JavaScript
PHP
Python
Ruby

JavaScript
Python

Server-side scripts

Stored procedures

View functions in JavaScript

user defined functions

yes

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

with a proxy-based framework, named couchdb-lounge

yes

Sharding

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

Multi-source replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

in-memory journaling

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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

Access rights for users and roles

Role-based access control

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