DBMS > Apache Impala vs. JanusGraph vs. Memgraph vs. Microsoft SQL Server vs. XTDB

System Properties Comparison Apache Impala vs. JanusGraph vs. Memgraph vs. Microsoft SQL Server vs. XTDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

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

Microsofts flagship relational DBMS

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

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Trend Chart

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	3.02
Rank	#98	Overall
	#8	Graph DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

impala.apache.org

janusgraph.org

memgraph.com

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

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

impala.apache.org/impala-docs.html

docs.janusgraph.org

memgraph.com/docs

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

www.xtdb.com/docs

Social network pages

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Linux Foundation; originally developed as Titan by Aurelius

Memgraph Ltd

Microsoft

Juxt Ltd.

Initial release

2013

2017

1989

2019

Current release

4.1.0, June 2022

0.6.3, February 2023

SQL Server 2022, November 2022

1.19, September 2021

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

commercial

restricted free version is available

Open Source

MIT License

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Java

C and C++

C++

Clojure

Server operating systems

Linux

Linux
OS X
Unix
Windows

Linux

Linux
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free and schema-optional

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Bolt protocol
Cypher query language

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

HTTP REST
JDBC

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
Java
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

Clojure
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

dynamic graph partitioning

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Multi-source replication using RAFT

yes, but depending on the SQL-Server Edition

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

relationships in graphs

yes

Transaction concepts

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

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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

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

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

User authentification and security via Rexster Graph Server

Users, roles and permissions

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Licensing and pricing models

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