DBMS > Google BigQuery vs. Kingbase vs. Memcached vs. SAP HANA vs. XTDB

System Properties Comparison Google BigQuery vs. Kingbase vs. Memcached vs. SAP HANA vs. XTDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

In-memory key-value store, originally intended for caching

In-memory, column based data store. Available as appliance or cloud service

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

cloud.google.com/bigquery

www.kingbase.com.cn

www.memcached.org

www.sap.com/products/hana.html

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

cloud.google.com/bigquery/docs

github.com/memcached/memcached/wiki

help.sap.com/hana

www.xtdb.com/docs

Developer

Google

BeiJing KINGBASE Information technologies inc.

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

SAP

Juxt Ltd.

Initial release

2010

1999

2003

2010

2019

Current release

V8.0, August 2021

1.6.25, March 2024

2.0 SPS07 (April 4, 2023), April 2023

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

BSD license

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and Java

Clojure

Server operating systems

hosted

Linux
Windows

FreeBSD
Linux
OS X
Unix
Windows

Appliance or cloud-service

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

Standard with numerous extensions

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

Proprietary protocol

JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

user defined functions

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash) and vertical partitioning

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Repcached, a Memcached patch, provides this functionallity

yes

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate 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

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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)

fine grained access rights according to SQL-standard

yes

using SASL (Simple Authentication and Security Layer) protocol

yes

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