DBMS > Apache Ignite vs. Google Cloud Spanner vs. Transwarp Hippo

System Properties Comparison Apache Ignite vs. Google Cloud Spanner vs. Transwarp Hippo

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Editorial information provided by DB-Engines

Name

Description

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.

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.

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Vector DBMS

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

Score	2.94
Rank	#85	Overall
	#11	Key-value stores
	#47	Relational DBMS

Score	2.80
Rank	#91	Overall
	#50	Relational DBMS

Score	0.00
Rank	#379	Overall
	#18	Vector DBMS

Website

ignite.apache.org

cloud.google.com/spanner

www.transwarp.cn/en/subproduct/hippo

Technical documentation

apacheignite.readme.io/docs

cloud.google.com/spanner/docs

Developer

Apache Software Foundation

Google

Initial release

2015

2017

2023

Current release

2.16.0, December 2023

1.0, May 2023

License

Commercial or Open Source

Open Source

Apache 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

C++, Java, .Net

C++

Server operating systems

Linux
OS X
Solaris
Windows

hosted

Linux
macOS

Data scheme

yes

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

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

yes

Query statements complying to ANSI 2011

APIs and other access methods

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

gRPC (using protocol buffers) API
JDBC

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

RESTful HTTP API

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

Go
Java
JavaScript (Node.js)
Python

C++
Java
Python

Server-side scripts

Stored procedures

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Multi-source replication with 3 replicas for regional instances.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

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

Transaction concepts

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

ACID

Strict serializable isolation

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

Security Hooks for custom implementations

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

Role based access control and fine grained access rights

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More resources

Recent citations in the news

GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2025
10 December 2024, PR Newswire

What is Apache Ignite? How is Apache Ignite Used?
18 July 2022, The Stack

Real-time in-memory OLTP and Analytics with Apache Ignite on AWS | Amazon Web Services
14 May 2016, AWS Blog

Getting Started With Apache Ignite
19 December 2015, DZone

Apache Ignite: An Overview
6 September 2023, Open Source For You

provided by Google News

Google Cloud adds graph processing to Spanner, SQL support to Bigtable
1 August 2024, InfoWorld

New features make Google's Spanner a database for AI
1 August 2024, TechTarget

Google Cloud adds graph and vector search features to Spanner database
2 August 2024, Techzine Europe

Google Cloud expands its database portfolio with new AI capabilities
1 August 2024, TechCrunch

Google Cloud announces new data innovations to support AI applications
1 August 2024, SiliconANGLE News

provided by Google News

10 top vector database options for similarity searches
8 August 2024, TechTarget

provided by Google News

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