DBMS > Axibase vs. GridDB vs. MaxDB vs. Memcached vs. Newts

System Properties Comparison Axibase vs. GridDB vs. MaxDB vs. Memcached vs. Newts

Editorial information provided by DB-Engines

Name

Description

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

Scalable in-memory time series database optimized for IoT and Big Data

A robust and reliable RDBMS optimized to run all major SAP solutions

In-memory key-value store, originally intended for caching

Time Series DBMS based on Cassandra

Primary database model

Secondary database models

Key-value store
Relational DBMS

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

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	2.09
Rank	#120	Overall
	#10	Time Series DBMS

Score	2.26
Rank	#114	Overall
	#55	Relational DBMS

Score	18.08
Rank	#32	Overall
	#4	Key-value stores

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Website

axibase.com/docs/atsd/finance

griddb.net

maxdb.sap.com

www.memcached.org

opennms.github.io/newts

Technical documentation

docs.griddb.net

maxdb.sap.com/documentation

github.com/memcached/memcached/wiki

github.com/OpenNMS/newts/wiki

Developer

Axibase Corporation

Toshiba Corporation

SAP, acquired from Software AG (Adabas-D) in 1997

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

OpenNMS Group

Initial release

2013

1984

2003

2014

Current release

15585

5.1, August 2022

7.9.10.12, February 2024

1.6.27, May 2024

License

Commercial or Open Source

commercial

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

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

commercial

Limited community edition free

Open Source

BSD license

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Java

Server operating systems

Linux

AIX
HP-UX
Linux
Solaris
Windows

FreeBSD
Linux
OS X
Unix
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

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

yes

numerical, string, blob, geometry, boolean, timestamp

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

SQL92, SQL-like TQL (Toshiba Query Language)

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
WebDAV

Proprietary protocol

HTTP REST
Java API

Supported programming languages

Go
Java
PHP
Python
R
Ruby

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net
C#
Java
Perl
PHP
Python

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

Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Repcached, a Memcached patch, provides this functionallity

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID at container level

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 for users can be defined per database

fine grained access rights according to SQL-standard

yes

using SASL (Simple Authentication and Security Layer) protocol

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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

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