DBMS > BigchainDB vs. GeoMesa vs. Google Cloud Datastore vs. H2 vs. TimesTen

System Properties Comparison BigchainDB vs. GeoMesa vs. Google Cloud Datastore vs. H2 vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

In-Memory RDBMS compatible to Oracle

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

www.bigchaindb.com

www.geomesa.org

cloud.google.com/datastore

www.h2database.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

bigchaindb.readthedocs.io/en/latest

www.geomesa.org/documentation/stable/user/index.html

cloud.google.com/datastore/docs

www.h2database.com/html/main.html

docs.oracle.com/database/timesten-18.1

Developer

CCRi and others

Google

Thomas Mueller

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2016

2014

2008

2005

1998

Current release

5.0.0, May 2024

2.2.220, July 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Apache License 2.0

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

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

Python

Scala

Java

Server operating systems

Linux

hosted

All OS with a Java VM

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (GQL)

yes

APIs and other access methods

CLI Client
RESTful HTTP API

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

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

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

Java

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

using Google App Engine

Java Stored Procedures and User-Defined Functions

PL/SQL

Triggers

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on storage layer

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

depending on storage layer

Multi-source replication using Paxos

With clustering: 2 database servers on different computers operate on identical copies of a database

Multi-source replication
Source-replica replication

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

depending on storage layer

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

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

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

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

by means of logfiles and checkpoints

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

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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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

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