DBMS > InfinityDB vs. JanusGraph vs. Memcached vs. Microsoft SQL Server

System Properties Comparison InfinityDB vs. JanusGraph vs. Memcached vs. Microsoft SQL Server

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Editorial information provided by DB-Engines

Name

Description

A Java embedded Key-Value Store which extends the Java Map interface

A Graph DBMS optimized for distributed clusters

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

In-memory key-value store, originally intended for caching

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	0.07
Rank	#359	Overall
	#54	Key-value stores

Score	1.91
Rank	#135	Overall
	#12	Graph DBMS

Score	20.74
Rank	#32	Overall
	#4	Key-value stores

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Website

boilerbay.com

janusgraph.org

www.memcached.org

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

Technical documentation

boilerbay.com/infinitydb/manual

docs.janusgraph.org

github.com/memcached/memcached/wiki

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

Developer

Boiler Bay Inc.

Linux Foundation; originally developed as Titan by Aurelius

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Microsoft

Initial release

2002

2017

2003

1989

Current release

4.0

0.6.3, February 2023

1.6.25, March 2024

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

BSD license

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

All OS with a Java VM

Linux
OS X
Unix
Windows

FreeBSD
Linux
OS X
Unix
Windows

Linux
Windows

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

yes

APIs and other access methods

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Proprietary protocol

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

Supported programming languages

Java

Clojure
Java
Python

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

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

none

yes

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

none

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

Repcached, a Memcached patch, provides this functionallity

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

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

User authentification and security via Rexster Graph Server

yes

using SASL (Simple Authentication and Security Layer) protocol

fine grained access rights according to SQL-standard

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