DBMS > DataFS vs. Google BigQuery vs. KairosDB vs. LMDB vs. Microsoft Azure Synapse Analytics

System Properties Comparison DataFS vs. Google BigQuery vs. KairosDB vs. LMDB vs. Microsoft Azure Synapse Analytics

Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Large scale data warehouse service with append-only tables

Distributed Time Series DBMS based on Cassandra or H2

A high performant, light-weight, embedded key-value database library

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Primary database model

Secondary database models

Graph DBMS

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

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	1.99
Rank	#125	Overall
	#21	Key-value stores

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Website

newdatabase.com

cloud.google.com/bigquery

github.com/kairosdb/kairosdb

www.symas.com/symas-embedded-database-lmdb

azure.microsoft.com/services/synapse-analytics

Technical documentation

dev.mobiland.com/Overview.xsp

cloud.google.com/bigquery/docs

kairosdb.github.io

www.lmdb.tech/doc

docs.microsoft.com/azure/synapse-analytics

Developer

Mobiland AG

Google

Symas

Microsoft

Initial release

2018

2010

2013

2011

2016

Current release

1.1.263, October 2022

1.2.2, November 2018

0.9.32, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

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

Java

C++

Server operating systems

Windows

hosted

Linux
OS X
Windows

Linux
Unix
Windows

hosted

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

RESTful HTTP/JSON API

Graphite protocol
HTTP REST
Telnet API

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
C
C#
C++
VB.Net

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java
JavaScript

Node.js
PHP
Python

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

C#
Java
PHP

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Transact SQL

Triggers

no, except callback-events from server when changes happened

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

none

Sharding

based on Cassandra

none

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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

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

Windows-Profile

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

Google Cloud Identity & Access Management (IAM)

simple password-based access control

yes

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