DBMS > Axibase vs. Cachelot.io vs. Geode vs. Google Cloud Bigtable vs. Microsoft SQL Server

System Properties Comparison Axibase vs. Cachelot.io vs. Geode vs. Google Cloud Bigtable vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Description

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

In-memory caching system

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

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Microsofts flagship relational DBMS

Primary database model

Time Series DBMS

Key-value store

Key-value store
Wide column store

Relational DBMS

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	0.04
Rank	#388	Overall
	#62	Key-value stores

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

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

axibase.com/docs/atsd/finance

cachelot.io

geode.apache.org

cloud.google.com/bigtable

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

Technical documentation

geode.apache.org/docs

cloud.google.com/bigtable/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

2015

2002

2015

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

Simplified BSD License

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

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Java

C++

Server operating systems

Linux

FreeBSD
Linux
OS X

All OS with a Java VM

the JDK (8 or later) is also required

hosted

Linux
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

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

Memcached protocol

Java Client API
Memcached protocol
RESTful HTTP API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

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

Supported programming languages

Go
Java
PHP
Python
R
Ruby

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

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

C#
C++
Go
Java
JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

yes

user defined functions

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

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

none

Multi-source replication

Internal replication in Colossus, and regional replication between two clusters in different zones

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

none

Eventual Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

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

Atomic single-row operations

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

fine grained access rights according to SQL-standard

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