DBMS > Google Cloud Datastore vs. Interbase vs. NCache vs. Redis vs. SAP SQL Anywhere

System Properties Comparison Google Cloud Datastore vs. Interbase vs. NCache vs. Redis vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Description

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

Light-weight proven RDBMS

originally from Borland

Open-Source and Enterprise in-memory Key-Value Store

Popular in-memory data platform used as a cache, message broker, and database that can be deployed on-premises, across clouds, and hybrid environments

Redis focuses on performance so most of its design decisions prioritize high performance and very low latencies.

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Document store

Relational DBMS

Key-value store

Multiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistence

Relational DBMS

Secondary database models

Document store
Search engine

Using distributed Lucene

Document store

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector DBMS

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

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	4.61
Rank	#72	Overall
	#39	Relational DBMS

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

Score	157.80
Rank	#6	Overall
	#1	Key-value stores

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

cloud.google.com/datastore

www.embarcadero.com/products/interbase

www.alachisoft.com/ncache

redis.com
redis.io

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

cloud.google.com/datastore/docs

docs.embarcadero.com/products/interbase

www.alachisoft.com/resources/docs

docs.redis.com/latest/index.html
redis.io/docs

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Google

Embarcadero

Alachisoft

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

SAP

formerly Sybase

Initial release

2008

1984

2005

2009

1992

Current release

InterBase 2020, December 2019

5.3.3, April 2024

7.2.5, May 2024

17, July 2015

License

Commercial or Open Source

commercial

Open Source

Enterprise Edition available

Open Source

source-available extensions (modules), commercial licenses for Redis Enterprise

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.

Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs.

Implementation language

C#, .NET, .NET Core, Java

Server operating systems

hosted

Android
iOS
Linux
OS X
Windows

Linux
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes, details here

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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.

export as XML data possible

yes

Secondary indexes

yes

with RediSearch module

yes

SQL

Support of SQL

SQL-like query language (GQL)

yes

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

with RediSQL module

yes

APIs and other access methods

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

ADO.NET
JDBC
ODBC

IDistributedCache
JCache
LINQ
Proprietary native API

proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

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

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

using Google App Engine

yes

Interbase procedure and trigger language

support for stored procedures with SQL-Server CLR

Lua; Redis Functions coming in Redis 7 (slides and Github)

yes, in C/C++, Java, .Net or Perl

Triggers

Callbacks using the Google Apps Engine

yes

Notifications

publish/subscribe channels provide some trigger functionality; RedisGears

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Sharding

Automatic hash-based sharding with support for hash-tags for manual sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

Interbase Change Views

yes, with selectable consistency level

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

through RedisGears

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
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Eventual Consistency
Causal consistency can be enabled in Active-Active databases
Strong consistency with Redis Raft
Strong eventual consistency with Active-Active

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

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

optimistic locking and pessimistic locking

Atomic execution of command blocks and scripts and optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

yes

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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)

fine grained access rights according to SQL-standard

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

Access Control Lists (ACLs): redis.io/docs/management/security/acl
LDAP and Role-Based Access Control (RBAC) for Redis Enterprise
Mutual TLS authentication: redis.io/docs/management/security/encryption
Password-based authentication

fine grained access rights according to SQL-standard

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