DBMS > EsgynDB vs. Google Cloud Spanner vs. PostgreSQL vs. TimescaleDB vs. Titan
System Properties Comparison EsgynDB vs. Google Cloud Spanner vs. PostgreSQL vs. TimescaleDB vs. Titan
Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Name | EsgynDB Xexclude from comparison | Google Cloud Spanner Xexclude from comparison | PostgreSQL Xexclude from comparison | TimescaleDB Xexclude from comparison | Titan Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion | 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. | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL | Titan is a Graph DBMS optimized for distributed clusters. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS | Relational DBMS | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | Time Series DBMS | Graph DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | Relational DBMS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | www.esgyn.cn | cloud.google.com/spanner | www.postgresql.org | www.timescale.com | github.com/thinkaurelius/titan | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | cloud.google.com/spanner/docs | www.postgresql.org/docs | docs.timescale.com | github.com/thinkaurelius/titan/wiki | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Esgyn | PostgreSQL Global Development Group www.postgresql.org/developer | Timescale | Aurelius, owned by DataStax | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2015 | 2017 | 1989 1989: Postgres, 1996: PostgreSQL | 2017 | 2012 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 16.3, May 2024 | 2.15.0, May 2024 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | commercial | Open Source BSD | Open Source Apache 2.0 | Open Source Apache license, version 2.0 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | C++, Java | C | C | Java | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux | hosted | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | Linux OS X Windows | Linux OS X Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | yes | numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types | 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 | yes specific XML-type available, but no XML query functionality. | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | yes | yes Query statements complying to ANSI 2011 | yes standard with numerous extensions | yes full PostgreSQL SQL syntax | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | ADO.NET JDBC ODBC | gRPC (using protocol buffers) API JDBC At present, JDBC supports read-only queries. No support for DDL or DML statements. RESTful HTTP API | ADO.NET JDBC native C library ODBC streaming API for large objects | ADO.NET JDBC native C library ODBC streaming API for large objects | Java API TinkerPop Blueprints TinkerPop Frames TinkerPop Gremlin TinkerPop Rexster | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | All languages supporting JDBC/ODBC/ADO.Net | Go Java JavaScript (Node.js) Python | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | .Net C C++ Delphi Java JDBC JavaScript Perl PHP Python R Ruby Scheme Tcl | Clojure Java Python | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | Java Stored Procedures | no | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | no | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | yes, across time and space (hash partitioning) attributes | yes via pluggable storage backends | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Multi-source replication between multi datacenters | Multi-source replication with 3 replicas for regional instances. | Source-replica replication other methods possible by using 3rd party extensions | Source-replica replication with hot standby and reads on replicas | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | yes | yes using Google Cloud Dataflow | no | no | yes via Faunus, a graph analytics engine | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate Consistency | Immediate Consistency | Immediate Consistency | Eventual Consistency Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes | yes by using interleaved tables, this features focuses more on performance improvements than on referential integrity | yes | yes | yes Relationships in graph | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | ACID Strict serializable isolation | ACID | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes | yes Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | no | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | fine grained access rights according to SQL-standard | Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM) | fine grained access rights according to SQL-standard | fine grained access rights according to SQL-standard | User authentification and security via Rexster Graph Server | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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EsgynDB | Google Cloud Spanner | PostgreSQL | TimescaleDB | Titan | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | 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 | Graph DBMS increased their popularity by 500% within the last 2 years Graph DBMSs are gaining in popularity faster than any other database category Google Improves Cloud Spanner: More Compute and Storage without Price Increase Google turns up the heat on AWS, claims Cloud Spanner is half the cost of DynamoDB Google makes its Cloud Spanner database service faster and more cost-efficient 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 PostgreSQL is Now Faster than Pinecone, 75% Cheaper, with New Open Source Extensions Timescale unveils high-performance AI vector database extensions for PostgreSQL A New Era AI Databases: PostgreSQL with pgvectorscale Outperforms Pinecone and Cuts Costs by 75% with New Open-Source Extensions PostgreSQL Tutorial: Definition, Commands, & Features Raise the bar on AI-powered app development with Azure Database for PostgreSQL provided by Google News TimescaleDB Is a Vector Database Now, Too Timescale Acquires PopSQL to Bring a Modern, Collaborative SQL GUI to PostgreSQL Developers Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data Timescale announces $15M investment and new enterprise version of TimescaleDB provided by Google News Amazon DynamoDB Storage Backend for Titan: Distributed Graph Database | Amazon Web Services Titan Graph Database Integration with DynamoDB: World-class Performance, Availability, and Scale for New Workloads JanusGraph Picks Up Where TitanDB Left Off DSE Graph review: Graph database does double duty Database Deep Dives: JanusGraph provided by Google News |
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