DBMS > Apache Hive vs. FoundationDB vs. Memgraph

System Properties Comparison Apache Hive vs. FoundationDB vs. Memgraph

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Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

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

Ordered key-value store. Core features are complimented by layers.

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

Primary database model

Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Graph DBMS

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

Score	75.77
Rank	#16	Overall
	#11	Relational DBMS

Score	0.89
Rank	#197	Overall
	#32	Document stores
	#29	Key-value stores
	#92	Relational DBMS

Score	2.54
Rank	#98	Overall
	#8	Graph DBMS

Website

hive.apache.org

github.com/apple/foundationdb

memgraph.com

Technical documentation

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

apple.github.io/foundationdb

memgraph.com/docs

Developer

Apache Software Foundation

initially developed by Facebook

FoundationDB

Memgraph Ltd

Initial release

2012

2013

2017

Current release

3.1.3, April 2022

6.2.28, November 2020

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

BSL 1.1; commercial license for enterprise edition available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

C and C++

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

some layers support schemas

schema-free and schema-optional

Typing

predefined data types such as float or date

yes

some layers support 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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

supported in specific SQL layer only

APIs and other access methods

JDBC
ODBC
Thrift

Bolt protocol
Cypher query language

Supported programming languages

C++
Java
PHP
Python

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

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

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

in SQL-layer only

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

dynamic graph partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Multi-source replication using RAFT

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

in SQL-layer only

yes

relationships in graphs

Transaction concepts

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

ACID

with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

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

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

Users, roles and permissions

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