DBMS > HEAVY.AI vs. Snowflake vs. Splunk vs. TerminusDB vs. Warp 10

System Properties Comparison HEAVY.AI vs. Snowflake vs. Splunk vs. TerminusDB vs. Warp 10

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

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

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

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	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

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

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

Technical documentation

docs.heavy.ai

docs.snowflake.net/manuals/index.html

docs.splunk.com/Documentation/Splunk

terminusdb.github.io/terminusdb/#

www.warp10.io/content/02_Getting_started

Developer

HEAVY.AI, Inc.

Snowflake Computing Inc.

Splunk Inc.

DataChemist Ltd.

SenX

Initial release

2016

2014

2003

2018

2015

Current release

5.10, January 2022

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

commercial

Limited free edition and free developer edition available

Open Source

GPL V3

Open Source

Apache License 2.0

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

Prolog, Rust

Java

Server operating systems

Linux

hosted

Linux
OS X
Solaris
Windows

Linux

Linux
OS X
Windows

Data scheme

yes

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

yes

schema-free

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

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

CLI Client
JDBC
ODBC

HTTP REST

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

HTTP API
Jupyter
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript (Node.js)
Python

C#
Java
JavaScript
PHP
Python
Ruby

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

yes

WarpScript

Triggers

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

yes

Sharding

Graph Partitioning

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Multi-source replication

Journaling Streams

selectable replication factor

based on HBase

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

based on HBase

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

in-memory journaling

yes

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

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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