DBMS > Google Cloud Datastore vs. Hive vs. Memgraph vs. Microsoft SQL Server

System Properties Comparison Google Cloud Datastore vs. Hive vs. Memgraph vs. Microsoft SQL Server

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Editorial information provided by DB-Engines

Name

Description

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

data warehouse software for querying and managing large distributed datasets, built on Hadoop

An open source graph database built for real-time streaming and compatible with Neo4j

Microsofts flagship relational DBMS

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	3.02
Rank	#98	Overall
	#8	Graph DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

cloud.google.com/datastore

hive.apache.org

memgraph.com

www.microsoft.com/en-us/sql-server

Technical documentation

cloud.google.com/datastore/docs

cwiki.apache.org/confluence/display/Hive/Home

memgraph.com/docs

learn.microsoft.com/en-US/sql/sql-server

Social network pages

Developer

Google

Apache Software Foundation

initially developed by Facebook

Memgraph Ltd

Microsoft

Initial release

2008

2012

2017

1989

Current release

3.1.3, April 2022

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

BSL 1.1; commercial license for enterprise edition available

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

C++

Server operating systems

hosted

All OS with a Java VM

Linux

Linux
Windows

Data scheme

schema-free

yes

schema-free and schema-optional

yes

Typing

predefined data types such as float or date

yes, details here

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

SQL

Support of SQL

SQL-like query language (GQL)

SQL-like DML and DDL statements

yes

APIs and other access methods

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

JDBC
ODBC
Thrift

Bolt protocol
Cypher query language

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++
Java
PHP
Python

.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

using Google App Engine

yes

user defined functions and integration of map-reduce

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

dynamic graph partitioning

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

selectable replication factor

Multi-source replication using RAFT

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

relationships in graphs

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

with periodic snapshot and write-ahead logging (WAL) of changes

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 for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users, groups and roles

Users, roles and permissions

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Memgraph directly connects to your streaming infrastructure so you and your team...
» more

Competitive advantages

Business Source License ensures a future for the Memgraph community MAGE algorithm...
» more

Typical application scenarios

Graph algorithms in bioinformatics Social network analysis Cryptocurrency network...
» more

Licensing and pricing models

You can check out our pricing model and licenses on the company website .
» more

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