DBMS > AgensGraph vs. Microsoft Azure Data Explorer vs. MongoDB vs. Solr vs. Sqrrl

System Properties Comparison AgensGraph vs. Microsoft Azure Data Explorer vs. MongoDB vs. Solr 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

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Fully managed big data interactive analytics platform

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

A widely used distributed, scalable search engine based on Apache Lucene

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

column oriented

Document store

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

Spatial DBMS

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

bitnine.net/agensgraph

azure.microsoft.com/services/data-explorer

www.mongodb.com

solr.apache.org

sqrrl.com

Technical documentation

bitnine.net/documentation

docs.microsoft.com/en-us/azure/data-explorer

www.mongodb.com/docs/manual

solr.apache.org/resources.html

Developer

Bitnine Global Inc.

Microsoft

MongoDB, Inc

Apache Software Foundation

Amazon

originally Sqrrl Data, Inc.

Initial release

2016

2019

2009

2006

2012

Current release

2.1, December 2018

cloud service with continuous releases

6.0.7, June 2023

9.6.0, April 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Open Source

Apache Version 2

commercial

Cloud-based only

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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Implementation language

C++

Java

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X
Solaris
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux

Data scheme

depending on used data model

Fixed schema with schema-less datatypes (dynamic)

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

yes

Dynamic Fields enables on-the-fly addition of new fields

schema-free

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

yes

supports customizable data types and automatic typing

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

Secondary indexes

yes

all fields are automatically indexed

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

Kusto Query Language (KQL), SQL subset

Read-only SQL queries via the MongoDB Atlas SQL Interface

Solr Parallel SQL Interface

APIs and other access methods

Cypher Query Language
JDBC

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Java API
RESTful HTTP/JSON API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

C
Java
JavaScript
Python

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

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

Yes, possible languages: KQL, Python, R

JavaScript

Java plugins

Triggers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

yes

in MongoDB Atlas only

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

Implicit feature of the cloud service

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

yes

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

yes

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Eventual Consistency

Immediate Consistency

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

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

ACID

Multi-document ACID Transactions with snapshot isolation

optimistic locking

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

In-memory capabilities

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

yes

In-memory storage engine introduced with MongoDB version 3.2

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Azure Active Directory Authentication

Access rights for users and roles

yes

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

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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