DBMS > Apache Impala vs. IBM Db2 Event Store vs. Lovefield vs. mSQL vs. Oracle

System Properties Comparison Apache Impala vs. IBM Db2 Event Store vs. Lovefield vs. mSQL vs. Oracle

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Distributed Event Store optimized for Internet of Things use cases

Embeddable relational database for web apps written in pure JavaScript

mSQL (Mini SQL) is a simple and lightweight RDBMS

Widely used RDBMS

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Relational 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	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Website

impala.apache.org

www.ibm.com/products/db2-event-store

google.github.io/lovefield

hughestech.com.au/products/msql

www.oracle.com/database

Technical documentation

impala.apache.org/impala-docs.html

www.ibm.com/docs/en/db2-event-store

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.oracle.com/en/database

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

IBM

Google

Hughes Technologies

Oracle

Initial release

2013

2017

2014

1994

1980

Current release

4.1.0, June 2022

2.0

2.1.12, February 2017

4.4, October 2021

23c, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free developer edition available

Open Source

Apache 2.0

commercial

free licenses can be provided

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C and C++

JavaScript

C and C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

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

tested with Chrome, Firefox, IE, Safari

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

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

Data scheme

yes

Schemaless in JSON and XML columns

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

SQL-like DML and DDL statements

yes

through the embedded Spark runtime

SQL-like query language

via JavaScript builder pattern

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

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

JavaScript

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

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

PL/SQL

also stored procedures in Java possible

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Active-active shard replication

none

Multi-source 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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

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

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

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