DBMS > Apache IoTDB vs. FoundationDB vs. GBase vs. Google Cloud Datastore vs. HyperSQL

System Properties Comparison Apache IoTDB vs. FoundationDB vs. GBase vs. Google Cloud Datastore vs. HyperSQL

Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

Ordered key-value store. Core features are complimented by layers.

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Primary database model

Time Series DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

Document store

Relational DBMS

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Website

iotdb.apache.org

github.com/apple/foundationdb

www.gbase.cn

cloud.google.com/datastore

hsqldb.org

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

apple.github.io/foundationdb

cloud.google.com/datastore/docs

hsqldb.org/web/hsqlDocsFrame.html

Developer

Apache Software Foundation

FoundationDB

General Data Technology Co., Ltd.

Google

Initial release

2018

2013

2004

2008

2001

Current release

1.1.0, April 2023

6.2.28, November 2020

GBase 8a, GBase 8s, GBase 8c

2.7.2, June 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Open Source

based on BSD license

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++

C, Java, Python

Java

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
OS X
Windows

Linux

hosted

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Data scheme

yes

schema-free

some layers support schemas

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

some layers support typing

yes

yes, details here

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 query language

supported in specific SQL layer only

Standard with numerous extensions

SQL-like query language (GQL)

yes

APIs and other access methods

JDBC
Native API

ADO.NET
C API
JDBC
ODBC

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

HTTP API

JDBC via HTTP
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

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

All languages supporting JDBC/ODBC
Java

Server-side scripts

Stored procedures

yes

in SQL-layer only

user defined functions

using Google App Engine

Java, SQL

Triggers

yes

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Sharding

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

yes

Multi-source replication using Paxos

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Linearizable consistency

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.

Immediate Consistency

Foreign keys

Referential integrity

in SQL-layer only

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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

yes

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

fine grained access rights according to SQL-standard

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