DBMS > DolphinDB vs. Graph Engine vs. Kinetica vs. MongoDB vs. Sqrrl

System Properties Comparison DolphinDB vs. Graph Engine vs. Kinetica vs. MongoDB 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

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Fully vectorized database across both GPUs and CPUs

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

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Time Series DBMS
Vector DBMS

Graph DBMS
Key-value store

Relational DBMS

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Relational DBMS

Spatial DBMS
Time Series DBMS

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

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

Score	2.72
Rank	#100	Overall
	#8	Time Series DBMS
	#5	Vector DBMS

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.42
Rank	#261	Overall
	#120	Relational DBMS

Score	410.24
Rank	#5	Overall
	#1	Document stores

Website

sqrrl.com

Technical documentation

docs.dolphindb.cn/en/help200/index.html

www.graphengine.io/docs/manual

docs.kinetica.com

www.mongodb.com/docs/manual

Developer

DolphinDB, Inc

Microsoft

Kinetica

MongoDB, Inc

Amazon

originally Sqrrl Data, Inc.

Initial release

2018

2010

2012

2009

2012

Current release

v2.00.4, January 2022

7.1, August 2021

7.0.5, January 2024

License

Commercial or Open Source

commercial

free community version available

Open Source

MIT License

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.

commercial

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

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Implementation language

C++

.NET and C

C, C++

C++

Java

Server operating systems

Linux
Windows

.NET

Linux

Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

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.

schema-free

Typing

predefined data types such as float or date

yes

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

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 query language

SQL-like DML and DDL statements

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

C#
C++
F#
Visual Basic

C++
Java
JavaScript (Node.js)
Python

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

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

JavaScript

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

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

yes

Source-replica replication

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

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

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

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

yes

Multi-document ACID Transactions with snapshot isolation

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

GPU vRAM or System RAM

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

Administrators, Users, Groups

Access rights for users and roles on table level

Access rights for users and roles

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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