DBMS > HEAVY.AI vs. Oracle NoSQL vs. Rockset vs. SQLite

System Properties Comparison HEAVY.AI vs. Oracle NoSQL vs. Rockset vs. SQLite

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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

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Document store
Key-value store
Relational DBMS

Document store

Relational DBMS

Secondary database models

Spatial DBMS

Relational DBMS
Search engine

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

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

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

www.oracle.com/database/nosql/technologies/nosql

rockset.com

www.sqlite.org

Technical documentation

docs.heavy.ai

docs.oracle.com/en/database/other-databases/nosql-database/index.html

docs.rockset.com

www.sqlite.org/docs.html

Developer

HEAVY.AI, Inc.

Oracle

Rockset

Dwayne Richard Hipp

Initial release

2016

2011

2019

2000

Current release

5.10, January 2022

24.1, May 2024

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

commercial

Open Source

Public Domain

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

Java

C++

Server operating systems

Linux

Linux
Solaris SPARC/x86

hosted

server-less

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

optional

dynamic typing

yes

not rigid because of 'dynamic typing' concept.

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.

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

Read-only SQL queries, including JOINs

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC
Thrift
Vega

RESTful HTTP API

HTTP REST

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

C
C#
Go
Java
JavaScript (Node.js)
Python

Go
Java
JavaScript (Node.js)
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

configurable

ACID within a storage node (=shard)

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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.

yes

off heap cache

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

Access rights for users and organizations can be defined via Rockset console

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