DBMS > ArcadeDB vs. Axibase vs. Badger vs. GBase vs. Google Cloud Datastore

System Properties Comparison ArcadeDB vs. Axibase vs. Badger vs. GBase vs. Google Cloud Datastore

Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

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

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

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

Score	0.10
Rank	#358	Overall
	#48	Document stores
	#38	Graph DBMS
	#52	Key-value stores
	#35	Time Series DBMS

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	4.36
Rank	#72	Overall
	#12	Document stores

Website

arcadedb.com

axibase.com/docs/atsd/finance

github.com/dgraph-io/badger

www.gbase.cn

cloud.google.com/datastore

Technical documentation

docs.arcadedb.com

godoc.org/github.com/dgraph-io/badger

cloud.google.com/datastore/docs

Developer

Arcade Data

Axibase Corporation

DGraph Labs

General Data Technology Co., Ltd.

Google

Initial release

2021

2013

2017

2004

2008

Current release

September 2021

15585

GBase 8a, GBase 8s, GBase 8c

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

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

Open Source

Apache 2.0

commercial

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, Java, Python

Server operating systems

All OS with a Java VM

Linux

BSD
Linux
OS X
Solaris
Windows

Linux

hosted

Data scheme

schema-free

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

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

yes

yes, details here

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, no joins

SQL-like query language

Standard with numerous extensions

SQL-like query language (GQL)

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

ADO.NET
C API
JDBC
ODBC

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

Supported programming languages

Java

Go
Java
PHP
Python
R
Ruby

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

using Google App Engine

Triggers

yes

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

Multi-source replication using Paxos

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Foreign keys

Referential integrity

yes

relationship in graphs

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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.

User concepts

Access control

yes

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

More information provided by the system vendor

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

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

The Ultimate ATV Test: Suzuki's King Quad 750 AXI Rugged Package vs. Alaska's Hunting Season
20 April 2021, Outdoor Life

provided by Google News

Best cloud storage of 2024
4 June 2024, TechRadar

Google Cloud Stops Exit Fees
12 January 2024, Spiceworks News and Insights

Inside Google’s strategic move to eliminate customer cloud data transfer fees
12 January 2024, Network World

BigID Data Intelligence Platform Now Available on Google Cloud Marketplace
6 November 2023, PR Newswire

Google says it'll stop charging fees to transfer data out of Google Cloud
11 January 2024, TechCrunch

provided by Google News

Share this page