DBMS > dBASE vs. Google Cloud Bigtable vs. HugeGraph vs. Microsoft Azure Cosmos DB vs. ObjectBox

System Properties Comparison dBASE vs. Google Cloud Bigtable vs. HugeGraph vs. Microsoft Azure Cosmos DB vs. ObjectBox

Editorial information provided by DB-Engines

Name

Description

dBase was one of the first databases with a development environment on PC's. Its latest version dBase V is still sold as dBase classic, which needs a DOS Emulation. The up-to-date product is dBase plus.

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

A fast-speed and highly-scalable Graph DBMS

Globally distributed, horizontally scalable, multi-model database service

Extremely fast embedded database for small devices, IoT and Mobile

Primary database model

Relational DBMS

Key-value store
Wide column store

Graph DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Object oriented DBMS

Secondary database models

Spatial DBMS

Time Series DBMS

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

Score	9.70
Rank	#44	Overall
	#28	Relational DBMS

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

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

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

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Website

www.dbase.com

cloud.google.com/bigtable

github.com/hugegraph
hugegraph.apache.org

azure.microsoft.com/services/cosmos-db

objectbox.io

Technical documentation

www.dbase.com/support/knowledgebase

cloud.google.com/bigtable/docs

hugegraph.apache.org/docs

learn.microsoft.com/azure/cosmos-db

docs.objectbox.io

Developer

Asthon Tate

Google

Baidu

Microsoft

ObjectBox Limited

Initial release

1979

2015

2018

2014

2017

Current release

dBASE 2019, 2019

0.9

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

Apache License 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

Java

C and C++

Server operating systems

DOS

dBase Classic
Windows

dBase Pro

hosted

Linux
macOS
Unix

hosted

Android
iOS
Linux
macOS
Windows

Data scheme

yes

schema-free

yes

schema-free

yes

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

also supports composite index and range index

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

none

The IDE can access other DBMS or ODBC-sources.

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

Java API
RESTful HTTP API
TinkerPop Gremlin

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

Proprietary native API

Supported programming languages

dBase proprietary IDE

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

Groovy
Java
Python

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

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

Server-side scripts

Stored procedures

The IDE can access stored procedures in other database systems.

asynchronous Gremlin script jobs

JavaScript

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

Implicit feature of the cloud service

online/offline synchronization between client and server

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

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

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

not for dBase internal data, but IDE does support transactions when accessing external DBMS

Atomic single-row operations

ACID

Multi-item ACID transactions with snapshot isolation within a partition

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 and roles

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

Users, roles and permissions

Access rights can be defined down to the item level

yes

More information provided by the system vendor

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