DBMS > Apache Impala vs. HarperDB vs. mSQL vs. Oracle vs. OrigoDB

System Properties Comparison Apache Impala vs. HarperDB vs. mSQL vs. Oracle vs. OrigoDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

mSQL (Mini SQL) is a simple and lightweight RDBMS

Widely used RDBMS

A fully ACID in-memory object graph database

Primary database model

Relational DBMS

Document store

Relational DBMS

Document store
Object oriented DBMS

Secondary database models

Document store

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

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Website

impala.apache.org

www.harperdb.io

hughestech.com.au/products/msql

www.oracle.com/database

origodb.com

Technical documentation

impala.apache.org/impala-docs.html

docs.harperdb.io/docs

docs.oracle.com/en/database

origodb.com/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

HarperDB

Hughes Technologies

Oracle

Robert Friberg et al

Initial release

2013

2017

1994

1980

2009

under the name LiveDB

Current release

4.1.0, June 2022

3.1, August 2021

4.4, October 2021

23c, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free community edition available

commercial

free licenses can be provided

commercial

restricted free version is available

Open Source

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++

Node.js

C and C++

Server operating systems

Linux

Linux
OS X

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

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

Linux
Windows

Data scheme

yes

dynamic schema

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

JSON data types

yes

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like data manipulation statements

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

.NET Client API
HTTP API
LINQ

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

C
C++
Delphi
Java
Perl
PHP
Tcl

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

.Net

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Custom Functions

since release 3.1

PL/SQL

also stored procedures in Java possible

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

A table resides as a whole on one (or more) nodes in a cluster

none

Sharding, horizontal partitioning

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

the nodes on which a table resides can be defined

none

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

Atomic execution of specific operations

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes

Write ahead log

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights for users and roles

fine grained access rights according to SQL-standard

Role based authorization

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.