DBMS > BigObject vs. Cachelot.io vs. Google Cloud Spanner vs. Kingbase vs. ObjectBox

System Properties Comparison BigObject vs. Cachelot.io vs. Google Cloud Spanner vs. Kingbase vs. ObjectBox

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

In-memory caching system

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

Extremely fast embedded database for small devices, IoT and Mobile

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

Relational DBMS

Object oriented DBMS

Secondary database models

Document store
Spatial DBMS

Time Series DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Website

bigobject.io

cachelot.io

cloud.google.com/spanner

www.kingbase.com.cn

objectbox.io

Technical documentation

docs.bigobject.io

cloud.google.com/spanner/docs

docs.objectbox.io

Developer

BigObject, Inc.

Google

BeiJing KINGBASE Information technologies inc.

ObjectBox Limited

Initial release

2015

2017

1999

2017

Current release

V8.0, August 2021

License

Commercial or Open Source

commercial

free community edition available

Open Source

Simplified BSD License

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

C++

C and Java

C and C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

FreeBSD
Linux
OS X

hosted

Linux
Windows

Android
iOS
Linux
macOS
Windows

Data scheme

yes

schema-free

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

Query statements complying to ANSI 2011

Standard with numerous extensions

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

Memcached protocol

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

Proprietary native API

Supported programming languages

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

Go
Java
JavaScript (Node.js)
Python

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

Lua

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication with 3 replicas for regional instances.

yes

online/offline synchronization between client and server

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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

ACID

Strict serializable isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

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