DBMS > BoltDB vs. Datomic vs. Google BigQuery vs. Hazelcast vs. NuoDB

System Properties Comparison BoltDB vs. Datomic vs. Google BigQuery vs. Hazelcast vs. NuoDB

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Large scale data warehouse service with append-only tables

A widely adopted in-memory data grid

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Website

github.com/boltdb/bolt

www.datomic.com

cloud.google.com/bigquery

hazelcast.com

www.3ds.com/nuodb-distributed-sql-database

Technical documentation

docs.datomic.com

cloud.google.com/bigquery/docs

hazelcast.org/imdg/docs

doc.nuodb.com

Developer

Cognitect

Google

Hazelcast

Dassault Systèmes

originally NuoDB, Inc.

Initial release

2013

2012

2010

2008

2013

Current release

1.0.6735, June 2023

5.3.6, November 2023

License

Commercial or Open Source

Open Source

MIT License

commercial

limited edition free

commercial

Open Source

Apache Version 2; commercial licenses available

commercial

limited edition free

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

Java

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

hosted

All OS with a Java VM

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Data scheme

schema-free

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

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

RESTful HTTP API

RESTful HTTP/JSON API

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

Clojure
Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

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

Server-side scripts

Stored procedures

yes

Transaction Functions

user defined functions

in JavaScript

yes

Event Listeners, Executor Services

Java, SQL

Triggers

By using transaction functions

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding

data is dynamically stored/cached on the nodes where it is read/written

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

Replicated Map

yes

Managed transparently by NuoDB

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Since BigQuery is designed for querying data

one or two-phase-commit; repeatable reads; read commited

ACID

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes

MVCC

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

Temporary table

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Role-based access control

Standard SQL roles/ privileges, Administrative Users

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