DBMS > Alibaba Cloud Table Store vs. AnzoGraph DB vs. Google Cloud Spanner vs. Linter vs. SAP HANA

System Properties Comparison Alibaba Cloud Table Store vs. AnzoGraph DB vs. Google Cloud Spanner vs. Linter vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

RDBMS for high security requirements

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

Primary database model

Wide column store

Graph DBMS
RDF store

Relational DBMS

Secondary database models

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	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

www.alibabacloud.com/product/table-store

cambridgesemantics.com/anzograph

cloud.google.com/spanner

linter.ru

www.sap.com/products/hana.html

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

cloud.google.com/spanner/docs

help.sap.com/hana

Developer

Alibaba

Cambridge Semantics

Google

relex.ru

SAP

Initial release

2016

2018

2017

1990

2010

Current release

2.3, January 2021

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

free trial version available

commercial

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

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

Implementation language

C and C++

Server operating systems

hosted

Linux

hosted

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

Appliance or cloud-service

Data scheme

schema-free

Schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

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

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

Query statements complying to ANSI 2011

yes

APIs and other access methods

HTTP API

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

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

JDBC
ODBC

Supported programming languages

Java
Python

C++
Java
Python

Go
Java
JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

proprietary syntax with the possibility to convert from PL/SQL

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Automatic sharding

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication in MPP-Cluster

Multi-source replication with 3 replicas for regional instances.

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in MPP-Cluster

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

Atomic single-row operations

ACID

Strict serializable isolation

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 rights based on subaccounts and tokens

Access rights for users and roles

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

yes

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