DBMS > Apache Impala vs. Memgraph vs. RDF4J vs. Snowflake vs. Splice Machine

System Properties Comparison Apache Impala vs. Memgraph vs. RDF4J vs. Snowflake vs. Splice Machine

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Cloud-based data warehousing service for structured and semi-structured data

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Secondary database models

Document store

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	3.19
Rank	#94	Overall
	#8	Graph DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

memgraph.com/docs

rdf4j.org/documentation

docs.snowflake.net/manuals/index.html

splicemachine.com/how-it-works

Social network pages

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Memgraph Ltd

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Snowflake Computing Inc.

Splice Machine

Initial release

2013

2017

2004

2014

Current release

4.1.0, June 2022

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

BSL 1.1; commercial license for enterprise edition available

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Open Source

AGPL 3.0, commercial license 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

C++

C and C++

Java

Server operating systems

Linux

Linux
OS X
Unix
Windows

hosted

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free and schema-optional

yes

RDF Schemas

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

Bolt protocol
Cypher query language

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

CLI Client
JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

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

Java
PHP
Python

JavaScript (Node.js)
Python

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

user defined functions

yes

Java

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

dynamic graph partitioning

none

yes

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication using RAFT

none

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Transaction concepts

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

ACID

with snapshot isolation

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

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

yes

in-memory storage is supported as well

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 Apache Sentry and Kerberos

Users, roles and permissions

Users with fine-grained authorization concept, user roles and pluggable authentication

Access rights for users, groups and roles 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...
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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 .
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