DBMS > Aerospike vs. Apache Druid vs. Google Cloud Spanner vs. MarkLogic vs. PostgreSQL
System Properties Comparison Aerospike vs. Apache Druid vs. Google Cloud Spanner vs. MarkLogic vs. PostgreSQL
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Name | Aerospike previously called Citrusleaf Xexclude from comparison | Apache Druid Xexclude from comparison | Google Cloud Spanner Xexclude from comparison | MarkLogic Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Flash-optimized In-memory NoSQL Database | Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data | 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. | Operational and transactional Enterprise NoSQL database | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store Graph DBMS leveraging Apache Tinkerpop Key-value store Spatial DBMS | Relational DBMS Time Series DBMS | Relational DBMS | Document store Native XML DBMS RDF store as of version 7 Search engine | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | aerospike.com | druid.apache.org | cloud.google.com/spanner | www.marklogic.com | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.aerospike.com | druid.apache.org/docs/latest/design | cloud.google.com/spanner/docs | docs.marklogic.com | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Developer | Aerospike | Apache Software Foundation and contributors | MarkLogic Corp. | PostgreSQL Global Development Group www.postgresql.org/developer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2012 | 2012 | 2017 | 2001 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 7.0, November 2023 | 29.0.1, April 2024 | 11.0, December 2022 | 16.3, May 2024 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache and AGPL Licenses; open sourced in June 2014; commercial Enterprise Edition available | Open Source Apache license v2 | commercial | commercial restricted free version is available | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | C | Java | C++ | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux | Linux OS X Unix | hosted | Linux OS X Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | yes schema-less columns are supported | yes | schema-free Schema can be enforced | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | yes | yes | 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. | no | no | no | yes | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | no | SQL for querying | yes Query statements complying to ANSI 2011 | yes SQL92 | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | JDBC Proprietary protocol TinkerPop Gremlin | JDBC RESTful HTTP/JSON API | gRPC (using protocol buffers) API JDBC At present, JDBC supports read-only queries. No support for DDL or DML statements. RESTful HTTP API | Java API Node.js Client API ODBC proprietary Optic API Proprietary Query API, introduced with version 9 RESTful HTTP API SPARQL WebDAV XDBC XQuery XSLT | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net C C# C++ Erlang Go Java JavaScript (Node.js) Lua Perl PHP Python Ruby | Clojure JavaScript PHP Python R Ruby Scala | Go Java JavaScript (Node.js) Python | C C# C++ Java JavaScript (Node.js) Perl PHP Python Ruby | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | user defined functions with Lua | no | no | yes via XQuery or JavaScript | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | no | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | Sharding manual/auto, time-based | Sharding | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | selectable replication factor | yes, via HDFS, S3 or other storage engines | Multi-source replication with 3 replicas for regional instances. | yes | Source-replica replication other methods possible by using 3rd party extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | yes Aerospike Aggregation Framework is similar to Map/Reduce | no | yes using Google Cloud Dataflow | yes via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency in cross-datacenter configuration and Immediate Consistency in local cluster configuration | Immediate Consistency | Immediate Consistency | Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | yes by using interleaved tables, this features focuses more on performance improvements than on referential integrity | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | Atomic execution of operations | no | ACID Strict serializable isolation | ACID can act as a resource manager in an XA/JTA transaction | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | no | no | yes, with Range Indexes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access rights for users and roles with Enterprise Edition only | RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system | Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM) | Role-based access control at the document and subdocument levels | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Aerospike previously called Citrusleaf | Apache Druid | Google Cloud Spanner | MarkLogic | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | Aerospike is an enterprise-class, NoSQL database solution delivering predictable... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Optimized for use with SSDs (solid-state hard drives) Scales horizontally and vertically... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Aerospike excels in mission-critical applications that have mixed read/write workloads... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Nielsen, Williams-Sonoma, Inmobi, AppNexus, Telco (confidential), Financial Services... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | Aerospike's combination of speed, scalability, and reliability delivers 10x performance... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | Subscription-based Enterprise Edition and free, open-source Community Edition » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | Aerospike a Winner in 2024 Business Sustainability Awards New Aerospike Release Lets Enterprises Consolidate Expensive Legacy Cache And Database Platforms Aerospike Recognized by Independent Research Firm Among Notable Vendors in Vector Databases Report Aerospike Closes $109M in Growth Capital from Sumeru Equity Partners Aerospike Achieves the new AWS Advertising and Marketing Technology Competency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Aerospike previously called Citrusleaf | Apache Druid | Google Cloud Spanner | MarkLogic | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Evaluating Hbase and Aerospike Solutions for Real-time System of Record | PostgreSQL is the DBMS of the Year 2023 Snowflake is the DBMS of the Year 2022, defending the title from last year Snowflake is the DBMS of the Year 2021 Aerospike raises $109M for its real-time database platform to capitalize on the AI boom Aerospike Raises $109M For Accelerated Database Development, Market Expansion Aerospike a Winner in 2024 Business Sustainability Awards Aerospike's New Release Cuts Costs by Enabling Hundreds of Caches on Small Clusters Aerospike reels in $109M to accelerate its high-speed database provided by Google News Apache Druid Wins Best Big Data Product in the 2023 BigDATAwire Readers' Choice Awards 'Lucifer' Botnet Turns Up the Heat on Apache Hadoop Servers New DDoS malware Attacking Apache Hadoop, & Druid Servers Imply Announces Automatic Schema Discovery for Apache Druid, Reinforcing Druid's Leadership for Real-Time ... Apache Druid Takes Its Place In The Pantheon Of Databases provided by Google News Google Improves Cloud Spanner: More Compute and Storage without Price Increase Google makes its Cloud Spanner database service faster and more cost-efficient Google turns up the heat on AWS, claims Cloud Spanner is half the cost of DynamoDB Google Cloud just fired a major volley at AWS as the cloud wars heat up Google Spanner: When Do You Need to Move to It? provided by Google News MarkLogic “The NoSQL Database”. In the MarkLogic Query Console, you can… | by Abhay Srivastava | Apr, 2024 Database Platform to Simplify Complex Data | Progress Marklogic AI can make logistics data as valuable as intelligence or operational data for mission success ABN AMRO Moves Progress-Powered Credit Store App to Azure Cloud; Achieves 40% Faster Data Processing, Lower ... Seven Quick Steps to Setting Up MarkLogic Server in Kubernetes provided by Google News How LeadSquared accelerated chatbot deployments with generative AI using Amazon Bedrock and Amazon Aurora ... EDB unveils EDB Postgres AI Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need Why PostgreSQL Is the Bedrock for the Future of Data General availability: Microsoft Entra ID integration with Azure Cosmos DB for PostgreSQL | Azure updates provided by Google News |
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