DBMS > Axibase vs. Google Cloud Datastore vs. Ingres vs. Machbase Neo

System Properties Comparison Axibase vs. Google Cloud Datastore vs. Ingres vs. Machbase Neo

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Well established RDBMS

TimeSeries DBMS for AIoT and BigData

Primary database model

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

Score	0.21
Rank	#308	Overall
	#25	Time Series DBMS

Score	4.13
Rank	#71	Overall
	#12	Document stores

Score	3.63
Rank	#79	Overall
	#43	Relational DBMS

Score	0.07
Rank	#348	Overall
	#34	Time Series DBMS

Website

axibase.com/docs/atsd/finance

cloud.google.com/datastore

www.actian.com/databases/ingres

machbase.com

Technical documentation

cloud.google.com/datastore/docs

docs.actian.com/ingres

machbase.com/dbms

Developer

Axibase Corporation

Google

Actian Corporation

Machbase

Initial release

2013

2008

1974

originally developed at University Berkely in early 1970s

2013

Current release

15585

12.0, July 2024

V8.0, August 2023

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

free test version available

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

Java

Server operating systems

Linux

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

yes, details here

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

SQL-like query language

SQL-like query language (GQL)

yes

SQL-like query language

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

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

Supported programming languages

Go
Java
PHP
Python
R
Ruby

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Server-side scripts

Stored procedures

yes

using Google App Engine

yes

Triggers

yes

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication using Paxos

Ingres Replicator

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

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

volatile and lookup table

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

simple password-based access control

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

The Ultimate ATV Test: Suzuki’s King Quad 750 AXI Rugged Package vs. Alaska’s Hunting Season
14 October 2020, Outdoor Life

provided by Google News

Google Cloud vs AWS: Which Cloud Computing Platform is Better?
11 September 2024, Cloudwards

Google Gets Rid of Fees To Transfer Data Out of Cloud Platform
12 January 2024, Spiceworks News and Insights

Best cloud storage of 2024
13 September 2024, TechRadar

What Is Google Cloud? Platform, Benefits & More Explained
11 September 2024, Cloudwards

Google App Engine
26 April 2024, TechTarget

provided by Google News

Actian Launches Ingres 12.0 Database
4 June 2024, PR Newswire

New startup from Postgres creator puts the database at heart of software stack
12 March 2024, TechCrunch

Postgres pioneer Michael Stonebraker promises to upend the database once more
26 December 2023, The Register

Actian Launches Ingres as a Fully-Managed Cloud Service
24 September 2021, Integration Developers

Actian Avalanche Real-Time Connected Data Warehouse adds integration
28 April 2020, TechTarget

provided by Google News

Share this page