DBMS > Axibase vs. Geode vs. Google BigQuery vs. Microsoft Azure Table Storage vs. Microsoft SQL Server

System Properties Comparison Axibase vs. Geode vs. Google BigQuery vs. Microsoft Azure Table Storage vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Description

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

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Large scale data warehouse service with append-only tables

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

Microsofts flagship relational DBMS

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

axibase.com/docs/atsd/finance

geode.apache.org

cloud.google.com/bigquery

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

www.microsoft.com/en-us/sql-server

Technical documentation

geode.apache.org/docs

cloud.google.com/bigquery/docs

learn.microsoft.com/en-US/sql/sql-server

Developer

Axibase Corporation

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Google

Microsoft

Initial release

2013

2002

2010

2012

1989

Current release

15585

1.1, February 2017

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

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

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C++

Server operating systems

Linux

All OS with a Java VM

the JDK (8 or later) is also required

hosted

Linux
Windows

Data scheme

yes

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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

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 query language

SQL-like query language (OQL)

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

Java Client API
Memcached protocol
RESTful HTTP API

RESTful HTTP/JSON API

RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

Go
Java
PHP
Python
R
Ruby

.Net
All JVM based languages
C++
Groovy
Java
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

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

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

yes

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

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes, on a single node

Since BigQuery is designed for querying data

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

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

User concepts

Access control

Access rights per client and object definable

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

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