DBMS > LevelDB vs. Microsoft SQL Server vs. Qdrant vs. TigerGraph vs. TimesTen

System Properties Comparison LevelDB vs. Microsoft SQL Server vs. Qdrant vs. TigerGraph vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

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

Microsofts flagship relational DBMS

A high-performance vector database with neural network or semantic-based matching

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

In-Memory RDBMS compatible to Oracle

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	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

github.com/google/leveldb

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

github.com/qdrant/qdrant
qdrant.tech

www.tigergraph.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

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

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

qdrant.tech/documentation

docs.tigergraph.com

docs.oracle.com/database/timesten-18.1

Developer

Google

Microsoft

Qdrant

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2011

1989

2021

2017

1998

Current release

1.23, February 2021

SQL Server 2022, November 2022

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

BSD

commercial

restricted free version is available

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Rust

C++

Server operating systems

Illumos
Linux
OS X
Windows

Linux
Windows

Docker
Linux
macOS
Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

yes

SQL-like query language (GSQL)

yes

APIs and other access methods

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

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

C++
Java

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

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

yes

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, but depending on the SQL-Server Edition

Collection-level replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency, tunable consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

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

with automatic compression on writes

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Key-based authentication

Role-based access control

fine grained access rights according to SQL-standard

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