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  1. Stackups
  2. Application & Data
  3. In-Memory Databases
  4. In Memory Databases
  5. CQEngine vs Tile38

CQEngine vs Tile38

OverviewComparisonAlternatives

Overview

Tile38
Tile38
Stacks17
Followers41
Votes0
GitHub Stars9.5K
Forks597
CQEngine
CQEngine
Stacks3
Followers22
Votes0
GitHub Stars1.8K
Forks255

CQEngine vs Tile38: What are the differences?

# Introduction
This Markdown code provides a comparison between CQEngine and Tile38, highlighting their key differences for users to make an informed decision.

1. **Data Model**: CQEngine is an in-memory indexed collection library for Java objects, allowing high-performance querying over collections. On the other hand, Tile38 is a geospatial database that specializes in storing and querying location-based data, making it ideal for applications requiring spatial querying capabilities.
2. **Querying Capabilities**: CQEngine offers powerful querying capabilities for Java objects, supporting various types of queries including complex predicate queries. In contrast, Tile38 excels in geospatial querying, with support for advanced spatial queries such as radius queries, bounding box queries, and proximity searches.
3. **Indexing Support**: CQEngine provides indexing support to enhance query performance by creating indexes on data fields for faster retrieval. In comparison, Tile38 utilizes spatial indexing techniques to optimize queries on location-based data, ensuring efficient retrieval of geospatial information.
4. **Integration**: CQEngine can be seamlessly integrated into Java applications as a library, allowing developers to leverage its querying capabilities within their existing codebase. Tile38, on the other hand, is a standalone geospatial database that can be used in conjunction with other databases to handle location-based data efficiently.
5. **Scalability**: CQEngine is primarily focused on providing fast in-memory querying capabilities for smaller datasets, making it suitable for applications requiring real-time querying over small to moderate-sized data collections. In contrast, Tile38 is designed for handling large-scale geospatial data sets efficiently, enabling applications to scale seamlessly as the data volume grows.
6. **Use Cases**: CQEngine is well-suited for applications that require complex querying and indexing of Java objects, such as in-memory cache systems or real-time data processing pipelines. Conversely, Tile38 is ideal for applications dealing with location-based services, geospatial analytics, and proximity-based querying, catering to use cases like fleet tracking, geofencing, and location-based notifications.

In Summary, CQEngine and Tile38 differ in their data model, querying capabilities, indexing support, integration options, scalability, and use cases, making them suitable for distinct application scenarios based on their specific requirements.

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Detailed Comparison

Tile38
Tile38
CQEngine
CQEngine

It is an open source (MIT licensed), in-memory geolocation data store, spatial index, and realtime geofence. It supports a variety of object types including lat/lon points, bounding boxes, XYZ tiles, Geohashes, and GeoJSON.

It is a NoSQL indexing and Query Engine, for retrieving objects matching SQL-like queries from Java collections, with ultra-low latency

Spatial index with search methods such as Nearby, Within, and Intersects; Realtime geofencing through webhooks or pub/sub channels; Object types of lat/lon, bbox, Geohash, GeoJSON, QuadKey, and XYZ tile; Support for lots of Clients Libraries written in many different languages; Variety of protocols, including http (curl), websockets, telnet, and the Redis RESP; Server responses are RESP or JSON; Full command line interface; Leader / follower replication; In-memory database that persists on disk
Ultra-fast; Query engine; No SQL
Statistics
GitHub Stars
9.5K
GitHub Stars
1.8K
GitHub Forks
597
GitHub Forks
255
Stacks
17
Stacks
3
Followers
41
Followers
22
Votes
0
Votes
0
Integrations
Erlang
Erlang
PHP
PHP
C++
C++
Clojure
Clojure
Swift
Swift
Windows
Windows
Node.js
Node.js
Linux
Linux
Java
Java
Python
Python
MongoDB
MongoDB
PostgreSQL
PostgreSQL
Fastify
Fastify
MySQL
MySQL

What are some alternatives to Tile38, CQEngine?

Redis

Redis

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.

Hazelcast

Hazelcast

With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution.

Aerospike

Aerospike

Aerospike is an open-source, modern database built from the ground up to push the limits of flash storage, processors and networks. It was designed to operate with predictable low latency at high throughput with uncompromising reliability – both high availability and ACID guarantees.

MemSQL

MemSQL

MemSQL converges transactions and analytics for sub-second data processing and reporting. Real-time businesses can build robust applications on a simple and scalable infrastructure that complements and extends existing data pipelines.

Apache Ignite

Apache Ignite

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

SAP HANA

SAP HANA

It is an application that uses in-memory database technology that allows the processing of massive amounts of real-time data in a short time. The in-memory computing engine allows it to process data stored in RAM as opposed to reading it from a disk.

VoltDB

VoltDB

VoltDB is a fundamental redesign of the RDBMS that provides unparalleled performance and scalability on bare-metal, virtualized and cloud infrastructures. VoltDB is a modern in-memory architecture that supports both SQL + Java with data durability and fault tolerance.

Tarantool

Tarantool

It is designed to give you the flexibility, scalability, and performance that you want, as well as the reliability and manageability that you need in mission-critical applications

Azure Redis Cache

Azure Redis Cache

It perfectly complements Azure database services such as Cosmos DB. It provides a cost-effective solution to scale read and write throughput of your data tier. Store and share database query results, session states, static contents, and more using a common cache-aside pattern.

KeyDB

KeyDB

KeyDB is a fully open source database that aims to make use of all hardware resources. KeyDB makes it possible to breach boundaries often dictated by price and complexity.

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