DBMS > Altibase vs. Datomic vs. Google BigQuery vs. Google Cloud Datastore

System Properties Comparison Altibase vs. Datomic vs. Google BigQuery vs. Google Cloud Datastore

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

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

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

Primary database model

Relational DBMS

Document store

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

Score	1.02
Rank	#189	Overall
	#88	Relational DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	4.36
Rank	#72	Overall
	#12	Document stores

Website

altibase.com

www.datomic.com

cloud.google.com/bigquery

cloud.google.com/datastore

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

docs.datomic.com

cloud.google.com/bigquery/docs

cloud.google.com/datastore/docs

Developer

Altibase

Cognitect

Google

Initial release

1999

2012

2010

2008

Current release

v7.3, 2023, August 2023

1.0.7075, December 2023

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

limited edition free

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

C++

Java, Clojure

Server operating systems

AIX
HP-UX
Linux

All OS with a Java VM

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL-92

yes

SQL-like query language (GQL)

APIs and other access methods

JDBC
ODBC
Proprietary protocol

RESTful HTTP API

RESTful HTTP/JSON API

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

Supported programming languages

C
C++
Java

Clojure
Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

Transaction Functions

user defined functions

in JavaScript

using Google App Engine

Triggers

yes

By using transaction functions

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

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

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

via ReferenceProperties or Ancestor paths

Transaction concepts

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

ACID

Since BigQuery is designed for querying 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

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

User concepts

Access control

fine grained access rights according to SQL-standard

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

Google Cloud Identity & Access Management (IAM)

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.