DBMS > Ingres vs. Machbase Neo vs. Microsoft Azure Table Storage vs. SQLite vs. TimesTen

System Properties Comparison Ingres vs. Machbase Neo vs. Microsoft Azure Table Storage vs. SQLite vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Well established RDBMS

TimeSeries DBMS for AIoT and BigData

A Wide Column Store for rapid development using massive semi-structured datasets

Widely used embeddable, in-process RDBMS

In-Memory RDBMS compatible to Oracle

Primary database model

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

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.actian.com/databases/ingres

machbase.com

azure.microsoft.com/en-us/services/storage/tables

www.sqlite.org

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

docs.actian.com/ingres

machbase.com/dbms

www.sqlite.org/docs.html

docs.oracle.com/database/timesten-18.1

Developer

Actian Corporation

Machbase

Microsoft

Dwayne Richard Hipp

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

1974

originally developed at University Berkely in early 1970s

2013

2012

2000

1998

Current release

11.2, May 2022

V8.0, August 2023

3.46.0 (23 May 2024), May 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

free test version available

commercial

Open Source

Public Domain

commercial

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

Server operating systems

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux
macOS
Windows

hosted

server-less

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

Data scheme

yes

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

yes

SQL-92 is not fully supported

yes

APIs and other access methods

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

Ingres Replicator

selectable replication factor

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

volatile and lookup table

yes

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

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.