DBMS > LeanXcale vs. Linter vs. Qdrant vs. RocksDB vs. SingleStore

System Properties Comparison LeanXcale vs. Linter vs. Qdrant vs. RocksDB vs. SingleStore

Editorial information provided by DB-Engines

Name

Description

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

RDBMS for high security requirements

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Primary database model

Key-value store
Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	5.60
Rank	#62	Overall
	#35	Relational DBMS

Website

www.leanxcale.com

linter.ru

github.com/qdrant/qdrant
qdrant.tech

rocksdb.org

www.singlestore.com

Technical documentation

qdrant.tech/documentation

github.com/facebook/rocksdb/wiki

docs.singlestore.com

Developer

LeanXcale

relex.ru

Qdrant

Facebook, Inc.

SingleStore Inc.

Initial release

2015

1990

2021

2013

Current release

8.11.4, April 2024

8.5, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

BSD

commercial

free developer edition 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.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

C and C++

Rust

C++

C++, Go

Server operating systems

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Docker
Linux
macOS
Windows

Linux

64 bit version required

Data scheme

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.

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

yes

through Apache Derby

yes

but no triggers and foreign keys

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

C++ API
Java API

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Supported programming languages

C
Java
Scala

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

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

C
C++
Go
Java
Perl
Python
Ruby

Bash
C
C#
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Collection-level replication

yes

Source-replica replication

stores two copies of each physical data partition on two separate nodes

MapReduce

Offers an API for user-defined Map/Reduce methods

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency, tunable consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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

Fine grained access control via users, groups and roles

More information provided by the system vendor

Specific characteristics

SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more

Competitive advantages

SingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more

Typical application scenarios

Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more

Key customers

IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more

Market metrics

Customers in various industries worldwide including US and International Industry...
» more

Licensing and pricing models

F ree Tier and Enterprise Edition
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.