DBMS > Google BigQuery vs. GridGain vs. LeanXcale vs. Qdrant vs. STSdb

System Properties Comparison Google BigQuery vs. GridGain vs. LeanXcale vs. Qdrant vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

GridGain is an in-memory computing platform, built on Apache Ignite

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

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Vector DBMS

Key-value store

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	1.28
Rank	#167	Overall
	#6	Vector DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

cloud.google.com/bigquery

www.gridgain.com

www.leanxcale.com

github.com/qdrant/qdrant
qdrant.tech

github.com/STSSoft/STSdb4

Technical documentation

cloud.google.com/bigquery/docs

www.gridgain.com/docs/index.html

qdrant.tech/documentation

Developer

Google

GridGain Systems, Inc.

LeanXcale

Qdrant

STS Soft SC

Initial release

2010

2007

2015

2021

2011

Current release

GridGain 8.5.1

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java, C++, .Net

Rust

Server operating systems

hosted

Linux
OS X
Solaris
Windows

Docker
Linux
macOS
Windows

Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

yes

primitive types and user defined types (classes)

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

SQL

Support of SQL

yes

ANSI-99 for query and DML statements, subset of DDL

yes

through Apache Derby

APIs and other access methods

RESTful HTTP/JSON API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

.NET Client API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

C
Java
Scala

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

C#
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes (compute grid and cache interceptors can be used instead)

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Collection-level replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Security Hooks for custom implementations

Key-based authentication

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