DBMS > Google Cloud Datastore vs. Ignite vs. Riak TS vs. SAP IQ vs. TigerGraph

System Properties Comparison Google Cloud Datastore vs. Ignite vs. Riak TS vs. SAP IQ vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

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

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Columnar RDBMS optimized for Big Data analytics

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Document store

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

column-oriented

Graph DBMS

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

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

cloud.google.com/datastore

ignite.apache.org

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

www.tigergraph.com

Technical documentation

cloud.google.com/datastore/docs

apacheignite.readme.io/docs

www.tiot.jp/riak-docs/riak/ts/latest

help.sap.com/docs/SAP_IQ

docs.tigergraph.com

Developer

Google

Apache Software Foundation

Open Source, formerly Basho Technologies

SAP, formerly Sybase

Initial release

2008

2015

1994

2017

Current release

Apache Ignite 2.6

3.0.0, September 2022

16.1 SPS04, April 2019

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

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

C++, Java, .Net

Erlang

C++

Server operating systems

hosted

Linux
OS X
Solaris
Windows

Linux
OS X

AIX
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

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

restricted

yes

SQL

Support of SQL

SQL-like query language (GQL)

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

yes, limited

yes

SQL-like query language (GSQL)

APIs and other access methods

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

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

HTTP API
Native Erlang Interface

ADO.NET
JDBC
ODBC
RESTful HTTP API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

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

C#
C++
Java
PHP
Python
Ruby
Scala

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C
C#
C++
Java
Perl
PHP
Python
Ruby

C++
Java

Server-side scripts

Stored procedures

using Google App Engine

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

Erlang

yes

Triggers

Callbacks using the Google Apps Engine

yes (cache interceptors and events)

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

yes (replicated cache)

selectable replication factor

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes (compute grid and hadoop accelerator)

yes

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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.

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

links between datasets can be stored

yes

Relationships in graphs

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

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

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

Role-based access control

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