DBMS > LokiJS vs. Microsoft SQL Server vs. QuestDB vs. SAP SQL Anywhere vs. Tarantool

System Properties Comparison LokiJS vs. Microsoft SQL Server vs. QuestDB vs. SAP SQL Anywhere vs. Tarantool

Editorial information provided by DB-Engines

Name

Description

In-memory JavaScript DBMS

Microsofts flagship relational DBMS

A high performance open source SQL database for time series data

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

Primary database model

Document store
Key-value store
Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

Spatial DBMS

with Tarantool/GIS extension

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

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	2.52
Rank	#109	Overall
	#9	Time Series DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	1.72
Rank	#144	Overall
	#25	Document stores
	#25	Key-value stores
	#66	Relational DBMS

Website

github.com/techfort/LokiJS

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

questdb.io

www.sap.com/products/technology-platform/sql-anywhere.html

www.tarantool.io

Technical documentation

techfort.github.io/LokiJS

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

questdb.io/docs

help.sap.com/docs/SAP_SQL_Anywhere

www.tarantool.io/en/doc

Developer

Microsoft

QuestDB Technology Inc

SAP

formerly Sybase

Initial release

2014

1989

2014

1992

2008

Current release

SQL Server 2022, November 2022

17, July 2015

2.10.0, May 2022

License

Commercial or Open Source

Open Source

commercial

restricted free version is available

Open Source

Apache 2.0

commercial

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

C++

Java (Zero-GC), C++, Rust

C and C++

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

Linux
Windows

Linux
macOS
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

BSD
Linux
macOS

Data scheme

schema-free

yes

schema-free via InfluxDB Line Protocol

yes

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

Typing

predefined data types such as float or date

yes

string, double, decimal, uuid, integer, blob, boolean, datetime

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

via views

yes

SQL

Support of SQL

yes

SQL with time-series extensions

yes

Full-featured ANSI SQL support

APIs and other access methods

JavaScript API

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

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

ADO.NET
HTTP API
JDBC
ODBC

Open binary protocol

Supported programming languages

JavaScript

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

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

View functions in JavaScript

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

yes, in C/C++, Java, .Net or Perl

Lua, C and SQL stored procedures

Triggers

yes

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

none

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

horizontal partitioning (by timestamps)

none

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, but depending on the SQL-Server Edition

Source-replica replication with eventual consistency

Source-replica replication

Database mirroring

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a single collection possible

ACID

ACID for single-table writes

ACID

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

yes, write ahead logging

In-memory capabilities

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

yes

through memory mapped files

yes

yes, full featured in-memory storage engine with persistence

User concepts

Access control

fine grained access rights according to SQL-standard

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

More information provided by the system vendor

Specific characteristics

Relational model with native time series support Column-based storage and time partitioned...
» more

Competitive advantages

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more

Typical application scenarios

Financial tick data Industrial IoT Application Metrics Monitoring
» more

Key customers

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more

Licensing and pricing models

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

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