DBMS > Datomic vs. LevelDB vs. Microsoft SQL Server vs. TigerGraph

System Properties Comparison Datomic vs. LevelDB vs. Microsoft SQL Server vs. TigerGraph

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Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Microsofts flagship relational DBMS

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

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	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

www.datomic.com

github.com/google/leveldb

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

www.tigergraph.com

Technical documentation

docs.datomic.com

github.com/google/leveldb/blob/main/doc/index.md

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

docs.tigergraph.com

Developer

Cognitect

Google

Microsoft

Initial release

2012

2011

1989

2017

Current release

1.0.7075, December 2023

1.23, February 2021

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

limited edition free

Open Source

BSD

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

Java, Clojure

C++

Server operating systems

All OS with a Java VM

Illumos
Linux
OS X
Windows

Linux
Windows

Linux

Data scheme

yes

schema-free

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

yes

SQL-like query language (GSQL)

APIs and other access methods

RESTful HTTP API

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

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

Clojure
Java

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

C++
Java

Server-side scripts

Stored procedures

yes

Transaction Functions

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

yes

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

with automatic compression on writes

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Role-based access control

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