DBMS > Apache Kylin vs. Graph Engine vs. Microsoft Azure Table Storage vs. SurrealDB

System Properties Comparison Apache Kylin vs. Graph Engine vs. Microsoft Azure Table Storage vs. SurrealDB

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Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

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

A Wide Column Store for rapid development using massive semi-structured datasets

A fully ACID transactional, developer-friendly, multi-model DBMS

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Wide column store

Document store
Graph DBMS

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

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	1.02
Rank	#190	Overall
	#33	Document stores
	#18	Graph DBMS

Website

kylin.apache.org

www.graphengine.io

azure.microsoft.com/en-us/services/storage/tables

surrealdb.com

Technical documentation

kylin.apache.org/docs

www.graphengine.io/docs/manual

surrealdb.com/docs

Developer

Apache Software Foundation, originally contributed from eBay Inc

Microsoft

SurrealDB Ltd

Initial release

2015

2010

2012

2022

Current release

3.1.0, July 2020

v1.5.0, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

MIT License

commercial

Open Source

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

.NET and C

Rust

Server operating systems

Linux

.NET

hosted

Linux
macOS
Windows

Data scheme

yes

schema-free

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

ANSI SQL for queries (using Apache Calcite)

SQL-like query language

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

C#
C++
F#
Visual Basic

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

optimistic locking

ACID

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

In-memory capabilities

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

yes

User concepts

Access control

Access rights based on private key authentication or shared access signatures

yes, based on authentication and database rules

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