DBMS > HEAVY.AI vs. Oracle vs. Splunk vs. Vitess

System Properties Comparison HEAVY.AI vs. Oracle vs. Splunk vs. Vitess

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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

Widely used RDBMS

Analytics Platform for Big Data

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Relational DBMS

Search engine

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Document store
Spatial DBMS

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

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

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

www.oracle.com/database

www.splunk.com

vitess.io

Technical documentation

docs.heavy.ai

docs.oracle.com/en/database

docs.splunk.com/Documentation/Splunk

vitess.io/docs

Developer

HEAVY.AI, Inc.

Oracle

Splunk Inc.

The Linux Foundation, PlanetScale

Initial release

2016

1980

2003

2013

Current release

5.10, January 2022

23c, September 2023

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

commercial

restricted free version is available

commercial

Limited free edition and free developer edition available

Open Source

Apache Version 2.0, commercial licenses available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++ and CUDA

C and C++

Server operating systems

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
OS X
Solaris
Windows

Docker
Linux
macOS

Data scheme

yes

Schemaless in JSON and XML columns

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

SQL

Support of SQL

yes

with proprietary extensions

Splunk Search Processing Language for search commands

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC
Thrift
Vega

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP REST

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

C#
Java
JavaScript
PHP
Python
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

PL/SQL

also stored procedures in Java possible

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication
Source-replica replication

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

isolation level can be parameterized

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

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

Users with fine-grained authorization concept

no user groups or roles

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