DBMS > Adabas vs. Axibase vs. Google Cloud Datastore vs. HugeGraph vs. Snowflake

System Properties Comparison Adabas vs. Axibase vs. Google Cloud Datastore vs. HugeGraph vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

OLTP - DBMS for mainframes and Linux/Unix/Windows environments

used typically together with the Natural programming platform

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

A fast-speed and highly-scalable Graph DBMS

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.softwareag.com/en_corporate/platform/adabas-natural.html

axibase.com/docs/atsd/finance

cloud.google.com/datastore

github.com/hugegraph
hugegraph.apache.org

www.snowflake.com

Technical documentation

cloud.google.com/datastore/docs

hugegraph.apache.org/docs

docs.snowflake.net/manuals/index.html

Developer

Software AG

Axibase Corporation

Google

Baidu

Snowflake Computing Inc.

Initial release

1971

2013

2008

2018

2014

Current release

15585

0.9

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

Open Source

Apache Version 2.0

commercial

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

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

hosted

Linux
macOS
Unix

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

yes, details here

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.

yes

Secondary indexes

yes

also supports composite index and range index

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL-like query language

SQL-like query language (GQL)

yes

APIs and other access methods

HTTP API

with add-on software Adabas SOA Gateway
SOAP-based API

with add-on software Adabas SOA Gateway

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

Java API
RESTful HTTP API
TinkerPop Gremlin

CLI Client
JDBC
ODBC

Supported programming languages

Natural

Go
Java
PHP
Python
R
Ruby

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Groovy
Java
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

in Natural

yes

using Google App Engine

asynchronous Gremlin script jobs

user defined functions

Triggers

yes

Callbacks using the Google Apps Engine

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

yes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas Vista

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Source-replica replication

Multi-source replication using Paxos

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

edges in graph

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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

only with OS-specific tools (e.g. IBM RACF, CA Top Secret)

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

Users, roles and permissions

Users with fine-grained authorization concept, user roles and pluggable authentication

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