DBMS > BaseX vs. Google BigQuery vs. Prometheus vs. Realm vs. Sqrrl

System Properties Comparison BaseX vs. Google BigQuery vs. Prometheus vs. Realm vs. Sqrrl

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

Large scale data warehouse service with append-only tables

Open-source Time Series DBMS and monitoring system

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

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

Score	1.84
Rank	#135	Overall
	#4	Native XML DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Website

basex.org

cloud.google.com/bigquery

prometheus.io

realm.io

sqrrl.com

Technical documentation

docs.basex.org

cloud.google.com/bigquery/docs

prometheus.io/docs

realm.io/docs

Developer

BaseX GmbH

Google

Realm, acquired by MongoDB in May 2019

Amazon

originally Sqrrl Data, Inc.

Initial release

2007

2010

2015

2014

2012

Current release

11.0, June 2024

License

Commercial or Open Source

Open Source

BSD license

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

Server operating systems

Linux
OS X
Windows

hosted

Linux
Windows

Android
Backend: server-less
iOS
Windows

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

XQuery supports types

yes

Numeric data only

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.

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

RESTful HTTP/JSON API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

.Net
Java

with Android only
Objective-C
React Native
Swift

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

runs within the applications so server-side scripts are unnecessary

Triggers

yes

via events

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

by Federation

none

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

Transaction concepts

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

multiple readers, single writer

Since BigQuery is designed for querying data

ACID

Atomic updates per row, document, or graph entity

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

In-Memory realm

User concepts

Access control

Users with fine-grained authorization concept on 4 levels

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

Google Cloud Identity & Access Management (IAM)

yes

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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