DBMS > BigObject vs. Datomic vs. Google BigQuery vs. Linter vs. MaxDB

System Properties Comparison BigObject vs. Datomic vs. Google BigQuery vs. Linter vs. MaxDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

RDBMS for high security requirements

A robust and reliable RDBMS optimized to run all major SAP solutions

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	2.32
Rank	#112	Overall
	#55	Relational DBMS

Website

bigobject.io

www.datomic.com

cloud.google.com/bigquery

linter.ru

maxdb.sap.com

Technical documentation

docs.bigobject.io

docs.datomic.com

cloud.google.com/bigquery/docs

maxdb.sap.com/documentation

Developer

BigObject, Inc.

Cognitect

Google

relex.ru

SAP, acquired from Software AG (Adabas-D) in 1997

Initial release

2015

2012

2010

1990

1984

Current release

1.0.6735, June 2023

7.9.10.12, February 2024

License

Commercial or Open Source

commercial

free community edition available

commercial

limited edition free

commercial

Limited community edition free

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, Clojure

C and C++

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)

All OS with a Java VM

hosted

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

RESTful HTTP API

RESTful HTTP/JSON API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

ADO.NET
JDBC
ODBC
WebDAV

Supported programming languages

Clojure
Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

.Net
C#
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

Lua

yes

Transaction Functions

user defined functions

in JavaScript

yes

proprietary syntax with the possibility to convert from PL/SQL

yes

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

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