DBMS > LeanXcale vs. Microsoft Access vs. Microsoft Azure Table Storage vs. NebulaGraph vs. RocksDB

System Properties Comparison LeanXcale vs. Microsoft Access vs. Microsoft Azure Table Storage vs. NebulaGraph vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

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

A distributed, linear scalable, high perfomant Graph DBMS

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Key-value store
Relational DBMS

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

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	2.23
Rank	#116	Overall
	#10	Graph DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

www.leanxcale.com

www.microsoft.com/en-us/microsoft-365/access

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

github.com/vesoft-inc/nebula
www.nebula-graph.io

rocksdb.org

Technical documentation

developer.microsoft.com/en-us/access

docs.nebula-graph.io

github.com/facebook/rocksdb/wiki

Developer

LeanXcale

Microsoft

Vesoft Inc.

Facebook, Inc.

Initial release

2015

1992

2012

2019

2013

Current release

1902 (16.0.11328.20222), March 2019

9.2.1, May 2024

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

commercial

Open Source

Apache Version 2.0 + Common Clause 1.0

Open Source

BSD

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

C++

Server operating systems

Windows

Not a real database server, but making use of DLLs

hosted

Linux

Data scheme

yes

schema-free

Strong typed schema

schema-free

Typing

predefined data types such as float or date

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

Nebula Graph internally uses the Key-Value store RocksDB for persistency. The vertices, edges, and their properties are stored as Key while their values are stored as Value. The primary indexes are per Key and secondary indexes are per Value.

SQL

Support of SQL

yes

through Apache Derby

yes

but not compliant to any SQL standard

SQL-like query language

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

ADO.NET
DAO
ODBC
OLE DB

RESTful HTTP API

Browser interface
console (shell)
Cypher Query Language
GO Object Graph Mapper
Java Object Graph Mapper
NGBatis

ORM framework for NebulaGraph and Spring-Boot
Proprietary native API
Python Object Graph Mapper
Query language nGQL

C++ API
Java API

Supported programming languages

C
Java
Scala

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

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

.Net
C++
Go
Java
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

user defined functions

Triggers

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

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

Causal Clustering using Raft protocol

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

but no files for transaction logging

optimistic locking

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

using RocksDB

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

a simple user-level security was built in till version Access 2003

Access rights based on private key authentication or shared access signatures

Role-based access control

More information provided by the system vendor

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Key customers

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Market metrics

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Licensing and pricing models

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