DBMS > Lovefield vs. MaxDB vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage vs. TinkerGraph

System Properties Comparison Lovefield vs. MaxDB vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

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

Globally distributed, horizontally scalable, multi-model database service

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

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Wide column store

Graph DBMS

Secondary database models

Spatial DBMS

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

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	2.26
Rank	#114	Overall
	#55	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	0.13
Rank	#345	Overall
	#35	Graph DBMS

Website

google.github.io/lovefield

maxdb.sap.com

azure.microsoft.com/services/cosmos-db

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

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

maxdb.sap.com/documentation

learn.microsoft.com/azure/cosmos-db

Developer

Google

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

Microsoft

Initial release

2014

1984

2014

2012

2009

Current release

2.1.12, February 2017

7.9.10.12, February 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Limited community edition free

commercial

Open Source

Apache 2.0

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

JavaScript

C++

Java

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

AIX
HP-UX
Linux
Solaris
Windows

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC
WebDAV

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

RESTful HTTP API

TinkerPop 3

Supported programming languages

JavaScript

.Net
C#
Java
Perl
PHP
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

Groovy
Java

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

Using read-only observers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

Implicit feature of the cloud service

yes

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

optional

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Access rights based on private key authentication or shared access signatures

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